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Volume 14, Number 3 Printed ISSN: 1095-6328PDF ISSN: 1528-2643

ACADEMY OF EDUCATIONAL LEADERSHIPJOURNAL

Michael ShurdenEditor

Lander University

Nancy NilesEditor

Lander University

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Academy of Educational Leadership Journal, Volume 14, Number 3, 2010

ACADEMY OF EDUCATIONAL LEADERSHIP JOURNALEDITORIAL BOARD MEMBERS

Michael Shurden EditorLander University

Nancy Niles, EditorLander University

Kavous ArdalanMarist CollegePoughkeepsie, New York

Michael HarrisEastern Michigan UniversityYpsilanti, Michigan

Katherine BarkerUniversity of South Florida St. PetersburgSt. Petersburg, Florida

Debbie BeardSoutheast Missouri State UniversityCape Girardeau, Missouri

Kanata JacksonHampton UniversityHampton, Virginia

Tim JohnstonMurray State UniversityMurray, Kentucky

Linda BresslerUniversity of Houston-DowntownHouston, Texas

Raghu KorrapatiWalden UniversityBlythewood, South Carolina

Doug CagwinLander UniversityGreenwood, South Carolina

Asghar NazemzadehUniversity of Houston-DowntownHouston, Texas

Charles EmeryErskine CollegeSouth Carolina

Robert PritchardRowan UniversityGlassboro, New Jersey

Jerry GarrettIndiana University Purdue University Fort WayneFort Wayne, Indiana

Tony SantellaErskine CollegeDue West, South Carolina

Doug GriderUniversity of Arkansas-Fort SmithFort Smith, Arkansas

Elizabeth E. GrandonUniversity of Bío-Bío Chile

Rassule HadidiUniversity of Illinois at SpringfieldSpringfield, Illinois

Mel SchnakeValdosta State UniversityValdosta, Georgia

Susan ShurdenLander UniversityGreenwood, South Carolina

Neil TerryWest Texas A&M UniversityCanyon, Texas

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ACADEMY OF EDUCATIONAL LEADERSHIPJOURNAL

CONTENTS

EDITORIAL BOARD MEMBERS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii

LETTER FROM THE EDITORS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi

TO CONSOLIDATE OR NOT TO CONSOLIDATE,THAT IS THE QUESTION: OPTIMAL SCHOOL SIZEAND TEACHER INCENTIVE CONTRACTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1Aaron Lowen, Grand Valley State UniversityM. Ryan Haley, University of Wisconsin – OshkoshNancy J. Burnett, University of Wisconsin – Oshkosh

STRATEGICALLY PLANNING CAMPUSES FOR THE“NEWER STUDENTS” IN HIGHER EDUCATION . . . . . . . . . . . . . . . . . . . . . . . . . . . 15Charles F. Falk, Northern Illinois University (retired)Bruce K. Blaylock, Radford University

JOB ORDER COSTING: A SIMULATION ANDVEHICLE FOR CONCEPTUAL DISCUSSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39Rochelle K. Greenberg, Florida State UniversityArnold Schneider, Georgia Institute of Technology

FACTORS INFLUENCING THE UNIVERSITYSELECTION OF INTERNATIONAL STUDENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59Cynthia M. Daily, University of Arkansas at Little RockStephanie Farewell, University of Arkansas at Little RockGaurav Kumar, University of Arkansas at Little Rock

CREATING ACTIVE LEARNING APPLICATIONS ANDOPPORTUNITIES FOR AN ON-LINE LEADERSHIPCOURSE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77Charles A. Griffin, Northern Arizona UniversityChris A. Lockwood, Northern Arizona University

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WHAT IS A BETTER PREDICTOR OF SUCCESS IN ANMBA PROGRAM:WORK EXPERIENCE OR THE GMAT? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91Michael H. Deis, Clayton State UniversityReza Kheirandish,Clayton State University

FACTORS INFLUENCING STUDENT PERFORMANCEIN THE INTRODUCTORY MANAGEMENT SCIENCECOURSE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99Kelwyn A. D’Souza, Hampton UniversitySharad K. Maheshwari, Hampton University

MOVING TOWARDS A CULTURALLY DIVERSEACCOUNTING PROFESSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121Elizabeth K. Jenkins, San Jose State UniversityMary F. Calegari, San Jose State University

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LETTER FROM THE EDITORS

Welcome to the Academy of Educational Leadership Journal. The editorial content of thisjournal is under the control of the Allied Academies, Inc., a non profit association of scholars whosepurpose is to encourage and support the advancement and exchange of knowledge, understandingand teaching throughout the world. The mission of the AELJ is to publish theoretical, empirical,practical or pedagogic manuscripts in education. Its objective is to expand the boundaries of theliterature by supporting the exchange of ideas and insights which further the understanding ofeducation.

The articles contained in this volume have been double blind refereed. The acceptance ratefor manuscripts in this issue, 25%, conforms to our editorial policies.

We intend to foster a supportive, mentoring effort on the part of the referees which will resultin encouraging and supporting writers. We welcome different viewpoints because in differences wefind learning; in differences we develop understanding; in differences we gain knowledge and indifferences we develop the discipline into a more comprehensive, less esoteric, and dynamic metier.

Information about the organization, its journals, and conferences are published on our website. In addition, we keep the web site updated with the latest activities of the organization. Pleasevisit our site and know that we welcome hearing from you at any time.

Michael ShurdenEditor

Lander University

Nancy NilesEditor

Lander University

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TO CONSOLIDATE OR NOT TO CONSOLIDATE,THAT IS THE QUESTION: OPTIMAL SCHOOL SIZE

AND TEACHER INCENTIVE CONTRACTS

Aaron Lowen, Grand Valley State UniversityM. Ryan Haley, University of Wisconsin – Oshkosh

Nancy J. Burnett, University of Wisconsin – Oshkosh

ABSTRACT

Given the realities of ever-tightening public budgets and the directives inherent in the NoChild Left Behind Act (2001) school districts have been required to do more (with more directaccountability) with less (funding) than ever before. These two forces are, of course, conflicting.One approach to the funding dilemma has districts consolidating schools in order to pool enrollmentand resources, in an attempt to reduce pressure to increase class size that would likely reducestudent achievement. Another is to create incentive contracts for teachers so that studentachievement would directly affect teacher salary. We introduce monitoring technology into anagency-based model of teacher incentive contracting to determine optimal school size, bringing bothsides of this debate together.

INTRODUCTION

Over the last few decades the US school system has received much attention fromresearchers and administrators on a variety of issues such as incentive pay and accountability(Holmstrom & Milgrom, 1991; Kane & Staiger, 2002); school size (Lee & Smith, 1997; Umphrey,2002); school consolidations (Antonucci, 1999); curriculum decisions (Goodlad & Su, 1992);education accessibility (Dunn, 1992); and overall school reform (Allen & Dale, 1995). The No ChildLeft Behind Act of 2001 motivates further research in to these areas of study. We bring togetherseveral facets of these discussions by examining the cross implications of optimal school size andconsolidations with incentive teacher pay and accountability in the classroom.

A general trend over the past century, and the main motivation for our inquiry, has been thewide-scale consolidation of elementary and secondary schools and districts. Enrollment per schoolhas substantially increased since 1900, from 62.44 to 506.29 while the number of districts hascorrespondingly decreased; see Table 1.

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Table 1: The Consolidation of Schools and Districts in the United Statesa

Year Enrollment # of Schools Enrollment/School # of Districts

1900 15,503,000 248,279 62.44 -

1945-50 25,111,000 - - 83,718

1980-01 40,877,000 85,982 475.41 15,912

2000-01 47,223,000 93,273 506.29 14,859a Source: United States Department of Education (2002).

While consolidation of disparate community schools is frequently justified by appealing toeconomies of scale, it has precipitated many difficulties. One such difficulty is the loss of teacherand curriculum control suffered by formerly localized school administrators and parents, losses thatcan be attributed to the increasing physical and bureaucratic distance between teachers,administrators, and parents.

To address these difficulties, various accountability schemes have been implemented inrecent years, including incentive pay. The general premise of incentive-pay is straightforward:replace the eroded control structure with a formal incentive structure that optimally aligns teachereffort with administrative objectives. Unfortunately, even within incentive pay paradigms, anynumber of pervasive inefficiencies can arise when designing and implementing an incentivecontract. For this reason, it is crucial that the design phase be guided by sound theory that is flexibleenough to incorporate the relevant institutional features of the education system. Designing just sucha framework and its implication on optimal school size is the focus of this paper.

Cutshall (2003) describes a number of recent political events that suggest a growing concernover the negative effects of consolidated schools, and thus a general call to open a serious dialogueabout optimal school sizes. In particular, there is an important interaction between incentivecontracts and optimal school size. Bard, Gardener, and Wieland (2005) provide an excellent reviewon the history of school consolidation in the US, issues, solutions, and the literature related tooptimal school size (see also Barker and Gump (1964), Driscoll, Halcoussis, and Svorny (2003),Garbarino (1980), and Lee and Smith (1997)). One conclusion of Bard, Gardener, and Wieland isthat the estimates of “optimal school size” range dramatically depending on researcher and timeperiod. Indeed, their further conclusion that the literature lacks a cohesive model for thedetermination of optimal school size partly motivates this work. While some of this work is basedon solid statistical analyses, others are case studies (i.e., Kirkpatrick (1998) notes that one of thepoorest of New York City's sub-districts moved from among the worst rated to among the best byre-creating schools with 200-300 students each). We add to this discussion by presenting a modelof optimal school size that incorporates the positive effects of incentive contracts and inspection(possibly by parents).

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The remainder of the paper is organized into five sections. In the following sections of thispaper, we present the context and background of the administrative realities surrounding decisionsabout incentive pay and school size, our principal-agent model of incentive contracting with anauditor, and finally an example that shows optimal school size based on reasonable numericalestimates of our model.

BACKGROUND

Debates regarding the effects of school consolidations are complex. There are multiple cost– benefit analyses in existence (see, for example, Nelson, 1985 and Bard, Gardener, & Wieland,2005, among many others). Arguments for consolidating often concentrate on financial savings fromthe reduction in fixed costs associated with building and maintenance, as well as from reducingquasi-fixed costs, such as salary, pensions, and health care plans from redundant support staff.Consolidation often results in combined classes or the replacement of several part timers for fewerfull time positions, especially for special offerings (such as guidance, art, music, etc) which reducesthe number of faculty needed while increasing the variety of course offerings. Drawbacks toconsolidation include “psychic costs” to reduced parental involvement in teaching andadministrative decisions, increased travel time for students (and direct bussing costs), increaseddiscipline problems, and elevated tensions between students and teachers (see Allen & Dale, 1995,for example).

One additional cost, of particular interest to policymakers and student advocates, is theerosion of superintendents’ ability to monitor and influence teaching. This propagates a disconnectbetween outcomes the superintendent desires and outcomes the teachers produce; in short, moralhazard problems arise. In the language of principal-agent theory, moral hazard occurs when aprincipal (such as a superintendent) is unable to view all the actions taken by an agent (such as ateacher) that are relevant to the successful completion of the principal's objective.1 Outcomes of theteacher’s actions, such as student scores on standardized tests, are observable by the superintendent,but the underlying effort is not.

At first glance, the superintendent's inability to observe how teachers allocate their effort inthe classroom may seem inconsequential. However, teachers under a myopic incentive contract oftenexperience pressure to “teach to the test”, which may increase standardized test scores in the short-term (e.g., by rote memorization) but may be inconsistent with long-term learning and retention.This outcome is a direct result of the superintendent’s inability to monitor effort and effect correctiveaction.

The superintendent can employ one of two tools to assure its objective is met. First, a list ofspecific dictates could be issued that, if followed, would compel the teachers to assume an effortchoice well aligned with the superintendent’s objective. This prescription functions relatively wellin small districts where compliance can be easily observed; the advent of consolidations, however,

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has rendered this option infeasible because of prohibitively high costs of enforcing and monitoringthe dictates.

The second option at the superintendent's disposal is to carefully construct an incentive-basedsystem that induces the efforts that the superintendent desires. Such a system, when properlyconstructed, is self-enforcing, thereby greatly reducing the need for costly monitoring andenforcement. Correspondingly, such a system would be much better suited to the administrativeneeds of superintendents in the new age of consolidated schools. The principal-agent formulationof this decision problem is designed to deliver the least-cost contract the superintendent can offerto induce teacher participation and cooperation. The construction of this principal-agent model isthe subject of the next section.

EMPIRICAL RESULTS OF INCENTIVE CONTRACTS

Unlike the debate concerning school consolidation, that of incentive contracts for teachers(also known as pay-for-performance or merit pay) has received much attention in the media. Thetheoretical literature (Datar, Kulp, & Lambert, 2001; Holmstrom & Milgrom, 1991; Kane & Staiger,2002) indicates directions for handling multidimensional measures of performance, team production,and incongruence between effort and outcomes in contract design, but with a few notable exceptionsthis theory has not been followed. This fundamental disconnection of theory and design renders aportion of the empirical literature moot; badly designed incentive structures result in misallocatedeffort and unfavorable outcomes such as cheating, “teaching to the test,” incorrectly classifyingstudents as special needs to remove them from the testing pool, and so on. Poor results from poorlydesigned incentives are not a condemnation of incentive contracts, only poorly-designed incentivecontracts.

Some evidence in favor of incentive contracts comes from more recent, individual merit-stylecontracts (Ding & Lehrer, 2000; Lavy, 2002; Lavy, 2004). Jacob (2002) provides a solid review ofthe recent empirical literature. In contrast, research that disparages incentive contracts oftenexamines structures with targeted outcomes that were not in line with desired teacher behavior (suchas being one-dimensional when multi-dimensional incentives were needed). In essence, it is thepoorly written contracts that lead to poor outcomes, not that all such incentive-based contracts arebad.

What they fail to note, however, is that incentives are often interpreted very narrowly, andat the lowest teacher cost of compliance. For example, Glewwe, Ilias, and Kremer (2003) report thatan incentive scheme designed to reward the teacher for higher student test scores did not increaseteacher attendance or the frequency of homework assignments, but did, in fact, increase the studenttests scores. Evidently, the teachers added test review sessions or some activity that specificallytargeted the test, but nothing more -- a likely case of teaching to the test. None of these results aresurprising. The incentive was to increase test scores, which it did, but was unlikely to actually

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increase learning. These other items were not improved upon because they were outside the purviewof the incentive structure.

Eberts, Hollenbeck, and Stone (2000) report that paying teachers to increase studentattendance in an alternative schooling environment did indeed increase student attendance, thoughnot necessarily to their educational benefit. In fact, the incentives resulted in more classroom partiesand field trips (both low effort ways for the teacher to increase attendance), with little improvementin student achievement (although the selection effect of reducing drop-outs obfuscated their results).

Thus, teachers respond to incentives in the ways that we would expect if we recognized theirstrategic nature. Instead of condemning incentive contracts on the basis of outcomes of poorlydesigned contracts, there is a need to test contracts that provide incentives consistent with desiredoutcomes and optimal contract theory. Given that the debate over the efficacy of teacher incentivecontracts is still under consideration by the public, we proceed with the assumption that well-designed teacher incentive contracts have the potential to create desirable teacher behavior andstudent outcomes.

THE CONTRACTING ENVIRONMENT

We begin the presentation of our baseline agency model with a number of basic assumptionsabout the decision environment. First, assume the teacher (agent) chooses effort levels a and b. Weuse a to denote the effort allocated to the teaching of testable knowledge, and b to denote the effortallocated to all other activities valued by the superintendent (principal), such as nurturing a love oflearning or instilling higher-order thinking skills.

Second, assume that the teacher has one unit of effort to be divided among these two tasks,and further assume that the teacher exhausts this unit on these tasks. This assumption is not entirelyinnocuous because it eliminates moral hazard associated with total effort exerted. However, moralhazard associated with misallocated effort remains.2

Third, to reflect differences in teaching effectiveness, we suppose that teachers are classifiedinto two types, high and low quality. Teachers, being human, will have an aversion to effort(aversion), which may vary with type. High levels of such aversion may be associated with low typeteachers. A second issue is how these teacher types map into classroom use, captured by the strictlypositive parameter cs. We define this parameter as “classroom shortcuts,” noting that teachers arenot able to significantly change daily classroom hours, as abandoning a classroom is a bit tooobvious a way to shirk. What teachers can do, however, is to employ any of a vast array ofclassroom shortcuts that reduce their overall effort, but do not increase student learning. While manyof these classroom shortcuts are time-honored practices employed even by the finest of teachers, andsometimes actually serve a useful purpose (allowing students some in-class time to work onassignments while the instructor is available for questions, for example), many of these practices canbe easily abused so that teachers simply do not work (or transfer out-of-class work like grading to

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in-class hours that should be used for instruction). Thus, even high quality teachers will havepositive levels of cs. The amount of cs (along with teacher type) determines how a teacher's effortmaps to student outcomes; higher values for cs map to lower levels of student performance, for agiven level of effort.

We presume that the superintendent knows the proportion of high quality teacher type (q)and how each type transforms effort into student outcomes. We also assume that the superintendentcannot directly observe teacher type prior to contracting. Verifiable student outcomes, which we willdenote as X, might be such things scores on standardized tests, which we assume are immediatelyobservable. The other teacher induced outcomes (perhaps measured by post-secondary educationaspirations and life-long intellectual curiosity) may be equally or more important than X, but aremore difficult to measure in the short run and, as such, are not available for use with incentivecontracting.

Fourth, assume that teachers have reservation wage, depending upon whether they are highor low quality teachers, which represents the opportunity cost of accepting the teaching positionoffered by the superintendent.

With these basic assumptions about the decision environment in hand, we turn to thepreference assumptions of our model. We assume the superintendent has preferences over outcomes(X versus the harder to measure outcomes, which are simply considered to be ‘all else’ or theremainder of superintendent preferences) and wishes to minimize wages. We assume that teachershave preferences over wages and effort allocated to tasks a and b.

We now turn to some standard assumptions about the contracting environment. First, allutility weights are strictly positive. Second, the only permissible payments (from superintendent toteacher) are those stated explicitly in the contract and there is no black-market or kickbacks of anykind. Third, we assume that teachers are not internally motivated to allocate effort exactly as desiredby the superintendent. Fourth, each teacher performs alone; that is, we assume away jointproduction. Finally, we make the following sequence of assumptions about the timing of the model:first, the teacher privately realizes his/her type and chooses to enter into a contract only when thattype will provide recompense at or above the relevant reservation wage; second, given the teacher’stype and the pending contract, the teacher divides their one unit of effort across tasks a and b; andthird, the immediately observable outcomes X are realized, and the teacher is paid in accordancewith the contract specifications. We assume that other outcomes are realized later and, hence, do notenter into the pay arrangement: it takes time for society to realize these other educational benefits.

In an optimal world, self reporting would mean no need for outside auditing of teacherperformance. Before school consolidation, the small school system was well controlled by a singleadministrative unit. Once this control is supplanted by a distant administration, direct controldiminishes. Within this “stretched out” bureaucracy, the superintendent needs a rule to enforce itsdictates. Again, in an ideal world, self reporting would supplant the need for any auditors externalto the classroom, however, this is untenable in the real world of education administration. Therefore,

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we propose that the superintendent introduce an auditor to enforce the contract between thesuperintendent and the teacher. The auditor can be conceptualized in a variety of ways; someexamples would be a task force, a review committee, a system of unit or department heads, or oneof many other systems of review. In this optimal world, we make the assumptions that the auditorperfectly observes teacher effort levels.

The auditor and the superintendent observe different information prior to the payment phaseof the contract. The auditor receives information about teacher effort levels a and b, as well asoutcome X, while the superintendent does not directly observe effort levels and only sees outcomeX, hence the auditor can deduce teacher type (high or low), while the superintendent cannot. It is theauditor's ability to obtain a more comprehensive information set that is crucial to the payment phaseof the contract.

The auditor's role in the contract mechanism is to relay to the superintendent teacher-specificeffort allocations. Therefore, the auditor's signal is used to ensure that the teachers receive their type-specific reservation wages. For example, suppose the auditor observes teachers allocating effort inthe desired way; the auditor would then relay this compliance to the superintendent; and the teacherwould receive the high-type payment. Conversely, if the auditor signals non-compliance (i.e., theteacher has not provided the correct allocation for their type), the teacher receives the low-typepayment.

We assume the auditor is indifferent to student outcomes, X, serving only to impartiallyenforce contracts. Here, the auditor serves as a truth-telling technology, only to be hired when thegain in superintendent utility is greater than or equal to the auditor's salary. There are utility gainsto this use of an auditor system. For instance, the high-type teacher is able to move from a uniformcontract that pays all teachers identically to one where he/she can reap the rewards of highperformance. There may even be utility gain by the low-type teacher, if the contract allows them toaccept the lower wage for less effort. It is obvious that the superintendent gains utility, as nowteacher types can be reflected in salary savings. To assess the total change in utility induced by theauditor, we must weigh each of these type-specific changes in utility by the expected number ofteachers of each type; this will depend upon the model’s parameterization (to be discussed in thenext section). As long as the gains exceed the auditor's reservation wage the auditor will be hired.

This expected utility gain also limits the number of teachers a single auditor (or single systemof auditors) can monitor. The auditor has a quadratic two-parameter (Aaversion and Aexponent) utilityfunction that describe its disutility from the number of teachers monitored. The superintendent thenuses this model of audited teacher incentive contracts along with expected benefit from monitoringto choose the optimal auditor/teacher ratio. For the situation where a single auditor evaluatesteachers, we express this optimal auditor/teacher ratio as optimal school size, which makes theauditor/teacher ratio the optimal number of classroom instructors per school. This aspect of ourmodel permits us to comment on optimal school size.

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A NUMERICAL EXAMPLE

When the superintendent cannot distinguish between teacher types a pooling contract is oftenused. Pooling is, however, a poor option for the superintendent because it entails high teacher wagesfor even low type teachers and has no incentive for teachers to align effort allocations with those ofthe superintendent. From the superintendent’s perspective, the auditing technology results in a bettereffort allocation and a reduction in teacher wages. Both changes increase the superintendent’s utilityrelative to the pooling option. Wages are lower for the low type because they can no longer keeptheir type hidden from the auditor.

To make this concrete we present the results of a specific parameterization, the values forwhich we list in Table 2. In this parameterization the teacher aversion-to-effort parameters (Aaversion)are 0.5 for both types. Classroom shortcuts (cs) are the exponent on effort in the teachers’ productionfunctions and are set at 0.50 for high types and 1.00 for low types (leading to output factors of0.5^0.50 = 0.707 for high type teachers and 0.5^1 = 0.5 for low type teachers). The superintendenthas preferences for immediate, verifiable student outcomes (X) such that X receives higher weightin the superintendent’s utility function (0.6) than do the other outcomes (0.4). High types areassumed to make up 75% of the teaching population, thus q equals 0.75. The auditor's aversion toteacher monitoring are characterized with (Aaversion) equal to 0.0001 as that job is envisioned to benothing but monitoring and (Aexponent) equal to 2.

Table 2: Numerical Example ValuesVariable Value

aversionH 0.5aversionL 0.5csH 0.5csL 1superintendent weight on observable outcomes 0.6q 0.75Aexponent 2Aaversion 0.0001

Table 3 shows outcomes using these parameter values for both the pooling contract and theincentive contract with an auditor.3 As discussed above, the superintendent receives higher utilityfrom both types of teachers under the incentive contract with an auditor since the teachers no longercommand information rents. Note how low-type teachers receive a lower wage than in the pooling

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case whereas high-type teachers receive a higher wage than the pooling case; i.e., good teachers arerewarded and poor teachers are not.

Table 3: Contract Outcomes for the Numerical Example

Variable Without Incentives or Auditor (poolingcontract)

With Incentive Contracts andAuditor

b,H 0.556 0.538

b,L 0.556 0.6

wageH 0.294 0.31

wageL 0.294 0.255

These simplified assumptions regarding teacher behavior and superintendent preferences canbe used to determine optimal school size (teacher/auditor ratio). This derives from the interactionof the increasing monitoring costs and the superintendent's linear gain in expected utility fromauditor-driven teacher compliance. This result is a significant break from the education literature,which takes an empirical approach to student performance and school size by looking at historicalperformance-size ratios and hypothesizing a de facto relationship. While this traditional empiricalapproach to discover the best performance-size mix is important and informative, the self-selectionof poorer (and often times lower performing) districts to consolidate to cut costs makes this approachproblematic.

The optimal school size with teacher incentive contracts occurs where the superintendent’sutility function is maximized. There are many widely-varying recommendations for school size inthe literature often conditional on the type of school being discussed. The strength of our approachis that we identify behavioral characteristics consistent with school sizes. For instance, our modelcan be modified to fit an individual policy maker's beliefs about auditing costs as well as preferenceweights on verifiable versus subjective teaching outcomes. Figure 1 shows the graphical details ofour model’s ability to represent returns to school size for the parameterization given in our example.Note that the model was calibrated to reflect the school size recommendations from the literature(200-300 students per school).

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Figure 1: Superintendent Utility Based on School Size Given Contract Enforcement with an Auditor

0

0.002

0.004

0.006

0.008

0.01

0.012

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

# Teachers

The approach of offering optimal contracts and having them enforced in decision-makingunits of optimal sizes is an important detail that must not be overlooked as the debate continues overconsolidating small schools, reforming public education with vouchers and schools of choice, andtrying to set standards and develop accountability among faculty and administrators.

DISCUSSION, CONCLUSIONS, AND TOPICS FOR FUTURE RESEARCH

Our primary argument is that consolidation of schools and districts creates control andmonitoring problems for the educational process. Examining these issues of moral hazard andmisallocated effort helps fill an important gap in the public debate on how to address the issuesraised by consolidation. The policy implication that follows is not necessarily to create smaller,geography-specific (“neighborhood”) schools. First, demographic fluctuations across and withinneighborhoods may make such a structure unsustainable. Second, while settlement patterns maygroup student families by demography and socioeconomic status, it is not obvious that they willshare attitudes toward school outcomes. A lack of cohesion within the constituent students’ familiesin the presence of a consolidated district would undermine such a grouping, especially in thepresence of a consolidated district. Un-consolidating school districts is also an unlikely solution

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given political and financial realities. Given the current structure, however, other solutions areavailable that address these economic issues.

While “choice” in education is generally touted as a solution, our model allows us toexamine the effects of these solutions on the issue of control within a well-defined framework.Voucher systems and charter schools (in their many forms) fit the model of control delineated here.These solutions address the control problem by allowing families with similar educational standardsand focus to form coalitions across neighborhood lines. If these systems allow schools to comeunder more direct control by a group of “homogeneous” student families (in the sense of attitudestoward student learning, not demography, socioeconomic status, or geographical neighborhood), the“superintendent” of our model then takes on these families’ attitudes. They have relatively precisepreferences that are more uniformly enforced by direct oversight; the first-best of a smaller schooland district. In this case the costs of inspection are borne by the community, and our model finds thelimits of school size based on these costs. In contrast to the “psychic costs” argument prevalent inthe education literature, we argue that this creates a monitoring efficiency, where the parents buyin and become part of the monitoring process.

In fact, proposed educational reform in Michigan extends a preexisting charter system topartition high schools into smaller ones: “$15 million for the 21st Century Schools Fund to helpMichigan school districts replace large, impersonal high schools that have low academicachievement and high dropout rates, with small high schools that use relationships, discipline, andrelevance to help at-risk kids achieve” (Granholm Signs Budget, 2008). This policy prescription issimilar to that by the Bill and Melinda Gates Foundation (VanderArk, 2002). Our analysis indicatesthat, unless there is either a partition of students by parent interests, or initiation of an educationalinspector, there is unlikely to be the increase in school quality desired.

While we feel our model provides a sound framing of incentive pay contracting with use ofa monitor within the educational system, we recognize a number of other interesting realities thatcould be incorporated into our model. First, it may be interesting to add shirking (or moral hazardwith respect to total effort) to the teacher's effort allocation problem. In general, however, teachersare not able to shirk in the same way as other workers (as leaving a classroom unattended is easilyverified), which is why we introduced the ideas of positive levels of classroom shortcuts (cs) intoour model with varying levels being used either constructively (by high type teachers) or negatively(by low type teachers). Including shirking would leave the basic results unchanged, but wouldrequire the superintendent to more heavily compensate both types to reduce shirking to a level wherethe marginal benefits of reducing shirking further is equal to the marginal cost of motivating theteacher.

A second interesting extension to our model would be the relaxation of the two-typeassumption. We side-stepped this reality here as the focus of our presentation was to clearlyhighlight the auditor's contributions to the contracting environment and to demonstrate the model's

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ability to prescribe (endogenously) an optimal school size (teacher-auditor ratio). Incorporatingadditional types would parallel the results here but with potentially higher inspection costs.

Two particularly interesting modeling extensions are deterministic student outcomes andauditor observations. In reality, teacher effort and quality can be obscured by events in student lives,the effects of other teachers, cheating on tests to manipulate student test scores, and so on.Moreover, no auditor can observe teacher behavior perfectly. Adding this fact to the model wouldsubstantially complicate the contracting details, which would then require a formalization of riskpreferences. However, these complications would not change the fundamental importance of theauditor, the need for a contract, or the endogenous realization of maximum and optimal school sizes(though it may change the exact number). An approach similar to that in Banker and Datar (1989)would be a useful guide should the modeling of an imperfect auditor be a consequentialconsideration.

The auditor may be imperfect in another way. Specifically, they may succumb to temptationssuch as cronyism, where they have preferences over who receives the higher wage, anddisobedience, where they have preferences over outcomes that are different from that of thesuperintendent. Either form of deviation would potentially destroy the auditing process, thus thecontracting authority must be mindful of this reality when designing the contract.

One interesting form of incentive contracting allows the principal to allocate a “bonus pool”of money to deserving agents. One paper in particular, Baiman and Rajan (1995), would be a goodguide for extending our model in this way. The necessary evaluation of relative (agent) performancecould be conducted using the techniques found in Holmstrom (1982) as well as Banerjee and Beggs(1989). Although this is an appealing extension, we would expect many charges of cronyism undersuch a system.

Finally, one could involve a series of teachers for each student (joint production) and try toseparate the contributions of individual teachers from the noise associated with accurately gaugingother outcomes (observing whether they stay out of prison, become gainfully employed, go tocollege, etc). A similar notion would be to model joint production between the teacher and theauditor, for which the mechanisms described in Glover (1994) would be a good guide.

In the end, however, we feel the basic principal-agent model we present forms a soundframework for thinking about these problems and for evaluating the corresponding policyimplications on school size.

ENDNOTES

1 To be clear, superintendent is the traditional “principal” in a principal-agent model; “teacher” is the traditional“agent”; and “auditor,” will refer to the intermediary between them.

2 Moral hazard with respect to total effort can be modeled with this framework if the superintendent feels itnecessary; however, it is our opinion that this will rarely be necessary as total effort measured as, say, an 8-hour

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workday or 40-hour workweek would be relatively easy to enforce and would thus be a minor concerncompared to the moral hazard problem associated with misallocated effort.

3 Wage outcomes here are normalized to a fraction. We have omitted the full model description for the sake ofbrevity and readability, an expanded version of the paper, including the formal model, is available in “SchoolConsolidations and Teacher Incentive Contracts,” SSRN working paper No. 1238586, August 2008.

REFERENCES

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Antonucci, M. (1999). Mission creep: How large school districts lose sight of the objective-student learning, AdTI issuebrief No. 176. Arlington, VA: The Alexis de Tocqueville Institution.

Baiman, S. & M.V. Rajan (1995). The informational advantages of discretionary bonus schemes. The AccountingReview, 70, 557-579.

Banerjee, A. & A. Beggs (1989). Efficiency in hierarchies: Implementing the first-best solution by sequential actions.Rand Journal of Economics, 20, 637-645.

Banker, R.D. & S.M. Datar (1989). Sensitivity, precision, and linear aggregation of signals for performance evaluation.Journal of Accounting Research, 27, 21-39.

Bard, J., J. Gardener & R. Wieland (2005). Rural School Consolidation Report. Lyons, NE: Center for Rural Affairs.

Barker, R. & P. Gump (1964). Big School, Small School. Palo Alto, CA: Stanford University Press.

Cutshall, S. (2003). Is smaller better? Techniques, 78, 22 (4 pages).

Datar, S., S.C. Kulp & R.A. Lambert (2001). Balancing performance measures. Journal of Accounting Research, 39,75-92.

Ding, W. & S.F. Lehrer (2000). Using performance incentives to reward the value added by educators: theory andevidence from China. Econometric Society World Congress 2000 Contributed Paper 1519.

Driscoll, D., D. Halcoussis & S. Svorny (2003). School district size and student performance. Economics of EducationReview, 22(2), 193-201.

Dunn, D.D. (1992). Every Child is Our Child: A Plan for Education that Leaves no Child Behind. Lafayette, Indiana:Dunn and Hargitt, Inc.

Eberts, R., K. Hollenbeck & J. Stone (2000). Teacher performance incentives and student outcomes. W.E. UpjohnInstitute Working Paper 00-65.

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Garbarino, J. (1980). Some thoughts on school size and its effect on adolescent development. Journal of Youth andAdolescence, 9(1), 19-31.

Glewwe, P., N. Ilias & M. Kremer (2003). Teacher incentives. NBER Working Paper 9671.

Glover, J. (1994). A simpler mechanism that stops agents from cheating. Journal of Economic Theory, 62, 221-229.

Goodlad, J.I. & Z. Su (1992). Organization of the curriculum. In P.W. Jackson (Ed.), Handbook of Research onCurriculum, (pp. 327-344). New York: Macmillan.

Granholm Signs Budget Increasing Funding for Schools; Targets Dropout Rate, Early Childhood Education. (August,2008). Retrieved September 2, 2008, from http://mi.gov/som/0,1607,7-192--197691--,00.html.

Holmstrom, B. (1982). Moral hazard in teams. Bell Journal of Economics, 13, 324-340.

Holmstrom, B. & P. Milgrom (1991). Multitask principal-agent analyses: incentive contracts, asset ownership, and jobdesign. Journal of Law, Economics, and Organization, 7 (special issue), 24-52.

Jacob, B.A. (2002). Accountability, incentives, and behavior: the impact of high-stakes testing in the Chicago publicschools. NBER Working Paper 8968.

Jacob, B.A. & S.D. Levitt (2003). Rotten apples: an investigation of the prevalence and predictors of teacher cheating.NBER Working Paper 9413.

Kane, T.J. & D.O. Staiger (2002). The promises and pitfalls of using imprecise school accountability measures. Journalof Economic Perspectives, 16, 91-114.

Kirkpatrick, D.W. (1998). School size - bigger is not better. Washington, D.C.: Vermonters for Better Education.

Lavy, V.C. (2002). Evaluating the effect of teachers' group performance incentives on pupil achievement. Journal ofPolitical Economy, 110, 1286-1317.

Lavy, V.C. (2004). Performance pay and teachers' effort, productivity, and grading ethics. NBER Working Paper10622.

Lee, V.E. & J.B. Smith (1997). High school size: which works best and for whom? Educational Evaluation and PolicyAnalysis, 19, 205-227.

Nelson, E. (1985). School consolidation. ERIC Digest Number 13.

Umphrey, J. (2002). Does school size matter? Principal Leadership, 2, 4.

United States Department of Education (2002). Digest of Education Statistics, 2002. Washington, D.C.: National Centerfor Education Statistics.

VanderArk, T. (2002). The case for small schools. Educational Leadership, 59(5), 55.

15


STRATEGICALLY PLANNING CAMPUSES FOR THE“NEWER STUDENTS” IN HIGHER EDUCATION

Charles F. Falk, Northern Illinois University (retired)Bruce K. Blaylock, Radford University

ABSTRACT

The “traditional” 18 – 22 year old, residential college student makes up only 16% of thestudents enrolled in public and private two- and four-year institutions. More than half of today’sstudents are older and are taking classes part-time. Over a million attend for-profit institutions andmillions more participate in postsecondary education experiences offered by corporate universities.Most work full or part-time, have little interest in out-of-class activities, and are very savvy aboutcomputer-based technologies. These are the “newer students” of higher education and representthe largest market segment of those who will attend college in the foreseeable future. It would seemthe drastic shift in market characteristics would be accompanied by strategic shifts in universityplanning. This paper considers how changes in college student body characteristics over the yearshave (or should have) prompted college leaders to alter their thinking about many aspects of campusofferings, facilities, operations, services, and pricing. We examined strategic plans of manyuniversities and conclude that although many recognize the changing characteristics of the potentialstudent population, many are pursuing strategies that may be strategically leading to their owndownfalls.

INTRODUCTION

“If colleges and universities are to survive in the troubled years ahead, a strong emphasis onplanning is essential (Kotler & Murphy, 1981).” Those words are as true today as they were almost30 years ago when they were first written. Steadily changing student populations, rapidlydeteriorating economic conditions, and continuously improving technologies will impact the“whom” and the “how” universities offer education.

This paper considers how changes in college student body characteristics should promptcollege leaders to alter their strategic thinking about many aspects of campus offerings, facilities,operations, services, and pricing. The attributes and behaviors of colleges and universities that madethem successful in the past may or may not be the same attributes and behaviors that will enablethem to be successful in the future. In order to be competitive, survive, and flourish someinstitutions will need to strategically plan on becoming very different places than they are currently.

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Three themes drive this conclusion: (1) population demographics, (2) the increased importance andchanging characteristics of non-traditional students on college campuses, and (3) the economics ofhigher education. The implications from advances in computer and telecommunications technologywill be considered throughout this discussion.

THEME ONE: DEMOGRAPHIC CHANGES MEAN STUDENT BODY CHANGES

Before considering the implications of demographic changes on strategic planning, it isuseful to review characteristics of “traditional students” that were served for so long, in such largenumbers, and who remain the focus of many universities’ strategic planning processes and workproduct.

A consensus in higher education literature suggests traditional students:

‚ Are mostly in the 18-22 age bracket and recent high school graduates (Strage,2008);

‚ Are, for the most part, people of the majority culture--white, non-Hispanic (Strage,2008);

‚ Plan to, or do attend school full time (Pascarella & Terenzini, 1998);‚ Plan to, or do take instruction on a ‘main’ campus instead of at extension centers

(Pascarella & Terenzini, 1998);‚ Frequently seek a “residential learning experience” (Pascarella & Terenzini, 1998);‚ Look for a “warm and fuzzy” campus environment where they can expect extensive

contact with “Mr. Chips”-like faculty members and advisors and with fellowstudents (Strage, 2008);

‚ Are interested co- and extra-curricular activities such as watching or participatingin intercollegiate athletics, bands, music and drama outlets, etc. (Lake & Pushchak,2006);

‚ Want significant campus-based social and entertainment options (like fraternitiesand sororities, clubs, academic societies, etc.) (Strage, 2008);

‚ Are quite concerned about the “reputation” and/or “prestige” of the college oruniversity (Pascarella & Terenzini, 1998);

‚ Can afford through personal resources, parent’s resources, or through an ability toborrow, high tuition and fees as may be charged (Lake & Pushchak, 2006);

‚ May place high value on preparation for careers or vocations; but may also placehigh value on the arts and sciences, on the humanities, on liberal education; andmay profess to have a “love of learning;”

‚ May be very aware of and interested in the college’s record of placing graduates ingood jobs and/or in high quality graduate programs in areas like law, medicine,science, etc (Lake & Puschak, 2006).

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Decline of “Traditional Student” Enrollment

Reasonable scholars may disagree about the degree to which “traditional” students have ordo not have all of these characteristics, but one fact is undeniable: traditional students are no longerthe majority on college campuses and their numbers will continue to decline. Today, traditionalstudents comprise only 16% of college students (U.S. Department of Education, 2008), more thanhalf are over the age of 25, and go to school part-time (Eduventures, 2008). Approximately aquarter are taking online courses and over a million attend for-profit institutions such as theUniversity of Phoenix, Argosy University, DeVry University, and others (Russo, 2006).

U.S. demographic studies reveal that the significant and steady growth in high schoolgraduates that began in 1992 and fueled great growth on college campuses, reached its peak in 2007-2008 (Prescott, 2008). From that point onward, the number of graduates, depending upon locationwithin the U.S., will either stabilize (projected for 12 states) or decline (projected for 28 states) (U.S.Department of Education, 2008). All remaining 20 states are projected to have growth of less than10%.

In the pool of individuals that represent the market for higher education programs offeredby post-secondary institutions, the proportion of the market represented by traditional students isdeclining. At the same time the diversity of the individuals in the same pool is increasing. Diversityat the high school student level quickly translates into diversity at the college campus level.Between 2004-2005 and 2014-2015 the following changes are predicted to occur at the secondaryschool level (Prescott, 2008):

‚ Hispanic graduates will increase by 54%‚ Asian/Pacific Islander graduates will increase by 32%‚ Black, non-Hispanic graduates will increase by 3%‚ American Indian/Alaska Native graduates will increase by 7%‚ White, non-Hispanic graduates will decline by 11%

The realities of college and university enrollments are inextricably tied to the populationstatistics and demographics for the nation. From patterns and trends reflected in the above data, itis reasonable to suggest that the major group of students who found their way to campuses in thepast—traditional students—will be fewer in number. To the extent that traditional students can bereplaced, the replacements will be less traditional; and they will bring different cultural orientations,needs, and expectations with them. Campus leaders must not only grasp the significance of thisdemographic change, but be prepared to make the significant recruiting changes that will benecessary to compete in a totally different environment.

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Strategic Impact of the Decline in “Traditional Student” Enrollment

The decline in the number of high school graduates and the diversification of thecharacteristics of future students will have a significant impact on “traditional student” enrollment,but not all institutions of higher learning will be affected the same way. Hundreds of colleges anduniversities have for decades depended upon high school graduates to go directly into highereducation and fill their classes. If this population is declining, what happens on college campuses?We suggest the following: First, unless traditional students are replaced by other types of students,there will be plenty of empty college classroom seats, which will lead to financial peril forinstitutions. Second, the instinctual response by many college administrators will be to increaseefforts to attract members of this diminished applicant pool, thus increasing competition fortraditional students as well as the marketing or recruiting costs related thereto. Third, many of thetraditional students remaining in the diminished applicant pool will likely seek to “trade up” byapplying for admission to “better” schools that they would not have considered before—places fromwhich they previously would have expected to receive only “rejection letters.”

Table 1. Informal Classification/Taxonomy of Colleges and Universities(A Perception of Quality Scale)*

Classification Connotes Comment

Tier 1 The best in the nation Very strong reputation; “star” faculty; great facilities; thesources of new knowledge, innovations, and inventions;enormous breadth of programs (especially at the doctoral level);and highly-selective admissions

Tier 2 Excellent Regional reputation; excellent faculty; breadth of programs;excellent facilities; appropriate accreditations; modest researchoutputs, selective admissions

Tier 3 Good Local reputation; only some of a large number of programsoffered may be noteworthy; adequate faculty; often very goodfacilities; teaching emphasis; slight interest in research; lessselective admission policies

Tier 4 Fair Limited reputation, faculty quality and credentials may beinconsistent; marginal facilities; no research; open admissions

Tier 5 Poor or Worse “Diploma Mills” unaccredited by any reputable accreditingbody; usually operating out of a P.O. Box; typically lacking anyfull time, qualified faculty members; limited or no substantiveeducational facilities.

*Community/junior colleges are not categorized in this exhibit.

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Like most products and services, colleges and universities are differentiated by perceivedand real levels of quality. The academy typically refers to these differences as tiers. Table 1 offersa taxonomy for consideration as a framework for viewing institutions of higher learning.

For the top colleges and universities, “Tier 1” schools, the need for adjustment may belimited. The “Ivy-League” universities and venerable institutions like, Stanford, Duke, Rice,Northwestern, Emory, Vanderbilt, Chicago, etc. will always get all of the applicants they need; andtheir admissions committees will continue to be in a position to offer seats to only a fraction of thosewho apply. It is quite likely that such schools are always going to be insulated from the vicissitudesof demographic change. The same can be said for the nation’s top public universities—places likeIllinois, Michigan, Berkeley, North Carolina, Virginia, etc.

For many smaller, private/independent colleges or universities, and for many of the publicuniversities that fall into Tiers 2 - 4, the challenge for campus leaders is often one of trying tostrategically change a college in ways that make it more like that of their much more esteemedcompetitors and, therefore, making it more likely that a college can recruit the “better” students ithopes to attract. These strategic actions may be thought of as attempts to improve the valueproposition for prospective students—promising more to students in exchange for the tuition andfees they will invest in their education. Many schools in tiers 2 – 4 are amassing debt to make thesechanges and improvements (for examples, see Gallagher, 2009; UC Newsroom, 2006; Phillips,2009).

Altering product and service mix strategies are common tactics used by campus leaders inattempts to attract more traditional students, in a market segment where the population is decliningand for which the competition is most intense. The product and service mix of a university is itsprograms, physical facilities, faculty members, and student support/development services. Theintent of adjusting the quality of the product and service mix is to convince prospective traditionalstudents that a given non-tier one college is more competitive with the higher tier schools than itmay have been in the past. Campus leaders at Tier 2 - 4 institutions may find out the hard way thatthey may be chasing goals they are unlikely to attain. Clearly, the decline in the number oftraditional students is more problematical for lower tier schools than for the elites because thedemand for education in the top tier schools is inelastic. The demand in "lesser institutions;"however, is quite elastic. The top tier schools will cannibalize the 2nd tier schools to fill the seatsat the tier one schools; and students who make the switch will be quite happy to adjust their aims--even if the prices are higher. The tier 2 schools will cannibalize the 3rd tier schools to fill seats intheir classrooms; and the 3rd tier schools will cannibalize the 4th tier schools to fill their classroomsseats. Even community colleges may hurt as four-years schools accept students they would not haveaccepted in the past who might have otherwise attended the two-year institutions. As theseadjustments occur, and as students behave rationally by enrolling in the better schools thatpreviously would not have admitted them, colleges and universities on the lower end of the“perception of quality” scale, will suffer enrollment shortfalls; thereby potentially placing them in

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financial jeopardy. This will be especially so for schools that have spent money aimed at increasingenrollments of traditional students, but which have, in the past, shown little interest in attracting andserving non-traditional students.

THEME 2: CHANGING STUDENT EXPECATIONS - ATTRACTING “NEW”AND “NEWER” NON-TRADITIONAL STUDENTS BY UNDERSTANDING

THEIR GOALS AND NEEDS

Based on the demographics cited, it is a near certainty that the “traditional” college studentpopulation is declining. It will likely become more difficult and more expensive to recruittraditional students who might actually agree to come to many campuses where they have alwaysbeen the majority. This means the relative importance of enrolling non-traditional students to fillseats formerly filled by traditional students will become more imperative than ever before. We haveasserted colleges and universities in lower tiered schools will be impacted most by this change. Tokeep their financial heads above the water, many down-market institutions will have to recruit andadmit larger numbers of students with different wants and desires than those they had previouslyrelied on to fill their classes. Thus, a logical question for these schools is, “Is it possible to recruitmore non-traditional students to make up for what the campus will likely lose as traditional studentschoose to go elsewhere, or if they choose to skip a traditional approach to earning a degreealtogether?” This section will address the strategic implications of answering that question.

“New” and “Newer” Non-traditional Students, Who are They?

If any institution wants to increase its attractiveness to potential non-traditional students, itis important for all of the “players” on a campus to know as much as possible about these segments(we argue) of the market for higher learning. When thinking about the non-traditional students, wewere reminded of a line of dialog repeated many times in the old “Butch Cassidy and the SundanceKid” film. The line was “Who are those people?” Well, for starters, the academic preparation ofthese students may be similar to those who have been admitted in the past, but their backgrounds,and current stations in life may be reflected in a much different set of expectations and needs thatthey required from the academic institution.

Societal, economic, and political changes all contributed to the rise of the “nontraditional”student. “The Allied victory in World War II, the decrease in blue-collar jobs, and changing genderattitudes encouraged members of minority racial groups, young people with low social-classstanding, and women to attend college (Bean & Metzner, 1985).” Among the first waves of non-traditional students was the horde of returning military service veterans who, under the auspices ofthe “GI Bill,” flooded college and university campuses following the close of WWII and after theKorean Conflict (Ogren, 2003). To differentiate among the cohorts of non-traditional students that

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will be discussed in the following narrative, this group has been labeled the “NTS-1” group, or theoriginal group of non-traditional students. When the GI’s (the NS-1 group) came through thecollege doors, campus leaders made many modifications to accommodate them. Some of thosecampus adjustments became institutionalized and benefited other non-traditional students who camelater. For example, financial aid and affirmative action increased the racial, class, and genderdiversity of American campuses in the 1960s. As the cohort of returning veterans moved throughthe higher education system, their number soon abated and institutions re-focused upon what theyhad done in the past: mainly serving traditional students. The small number of remaining non-traditional students on campuses again experienced an education environment in which they wereexpected to “bend” to meet the schedules and policies of the institution instead of having theinstitution “bending” to meet the student’s needs.

By about 1970 things began to change again. A much larger number of non-traditionalstudents began to appear on college campuses. This development elevated the impact and thesignificance of this category of students to an unprecedented level. Higher education scholars gavethe 1970s’ – 1980s wave of non-traditional students the label of “the New Students in HigherEducation.” This cohort is referred to as the “NS-2” group in this paper. To be classified as amember of the NS-2 cohort of non-traditional students, one or more of the following descriptorswould have to be observable in the student’s status:

1. Being older than typical college student ages (usually age 25 or greater); 2. Classified as a part-time student;3. Not financially dependent on parents; 4. Work full time while enrolled; 5. Have dependents;6. Are single parents; and 7. Are recipients of a GED or high school completion certificate. (National Center for

Education Statistics, 2002).

The differences in characteristics between traditional and “new non-traditional” studentsmeant that the non-traditional student cohorts came to campuses with different needs andexpectations of the institutions with which they became affiliated. The following list identifiestypical wants and needs of this group.

‚ New non-traditional students:‚ Frequently want the ability to take instruction during the evening, on Saturdays, or

on the weekends;‚ Are interested in less than full-time study;

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‚ Often seek off-campus classes (at extension centers) where they can take instructionat sites that are closer to either their home or work;

‚ Seek “discounted” tuition because they feel they don’t ask for, or need, manycampus services which are in place largely to serve traditional students;

‚ Seek “student-friendly” course transfer-in policies (because they often startedcourse work years ago elsewhere; and/or because they move around a lot due to jobtransfers);

‚ Want access to ways of earning credits for “life experience” or “work experience”so as to short-cut the time to degree-completion;

‚ Expect eligibility for institutional financial aid;‚ Want institutions to sensibly offer all of the classes that make it possible for a student

to earn full degrees in selected areas solely by studying part-time, or in the evening,or on Saturdays, or in weekend or off-campus classes;

‚ Expect to have campus support services, such as counseling; food service;bookstore; bill paying, transcript requests; advising; and tutoring assistance,available when and where non-traditional students are on the campus—at night,Saturdays, etc;

‚ Have only limited interest in the out-of-class opportunities such as student clubs,student government, theatricals, fraternities/sororities, and athletics that areavailable and of interest to the “traditional” students;

‚ Believe that a college or university’s “reputation” and its high-quality or “star”faculty is of some importance to them; but the convenience of learning and havingthe chance to get to degree-completion as fast as possible is more important for them(This is of the sharpest points of divergence between the traditional and non-traditional student);and

‚ Are highly-focused upon what their program will do to establish them in a careerand/or enhance their path along a career they’ve already chosen to pursue.

Soon, it wasn’t hard to find professional articles appearing in many venues that suggestedhow campus leaders should adapt what they did to meet the needs of this growing student populationgroup (See Aslanian, 1980; Brazziel, 1989; Levine & Nidiffer, 1996; Pascarella & Terenzini, 1998,and London, 1992). Over time the “new students” in higher learning”—first the NS-1 group and,later, the NS-2 group--were no longer the oddities on campuses that they once were. They becamefully-assimilated into the life, work, and systems of the institutions where they studied. At manyinstitutions, NS-1 and NS-2 students, despite their differences from higher education’s first clientele,became the modern-day traditional students.

In the 1990s, as the millennium approached, yet a different group of non traditional studentsbegan to emerge. This group, to whom we refer as “newer students,” is also discussed by Obligner(2003). She reported that the group included “Boomers, Gen-Xers, and Millenials.” Further, she

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asserted that each component of this triumvirate brought different traits and expectations to the tablewhen then entered campuses and classrooms. The writers have, however, chosen homogenize thisgroup and to call it the “newer students” cohort of nontraditional students and we’ve labeled thegroup as “NS-3” in this paper. The NS-3 cohort has some attributes in common with the NS-2cohort, but this latest group to arrive on campuses brought their own unique characteristics withthem. Given population demographic trends, it is likely that this latest group to appear in the higherlearning marketplace will be both increasingly more significant in numbers and also more significantin terms of their likely influence on college campuses.

A profile of the characteristics of the “newer” students (NS-3 cohort) is described in thefollowing list:

‚ The “Newer Students in Higher Learning”‚ Often are foreign born. If not foreign born, their parents are; and they may well be

the first person in their family attempting a college experience;‚ Often use English as their second language; having been reared with another

language being the first language spoken in their homes;‚ Frequently have meager financial resources;‚ Often work minimum wage jobs; and do not have access to employer-sponsored

employee tuition assistance programs; and‚ Typically have extensive needs for remedial/developmental education (English

language proficiency, writing skills, reading skills, study skills, math competency,etc.) in multiple areas.

Along with these characteristics come a different set of expectations from the NS-3 non-traditional student. Table 2 compares the wants and needs of the NS-2 and NS-3 non-traditionalstudents.

Table 2 Campus/Program Characteristics of Interest or Concern to Students:Comparing the “new” and “newer” non-traditional students

Campus/Program Characteristics of Interest or Concern toStudents

Importance to theNS-2 Cohort


Out-of-class and/or extra-curricular activities (especially ifthey would require a student to come to a campus on a day ofthe week or at time of day when they would not plan to be oncampus to begin with)

Low Importance Not Important

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Table 2 Campus/Program Characteristics of Interest or Concern to Students:Comparing the “new” and “newer” non-traditional students

Campus/Program Characteristics of Interest or Concern toStudents




Ability to classes full time instead of just taking classes on apart-time basis

Not Important Important

Ability to enroll in day-time courses because they may workfull or part-time in evening jobs. (This is a big point ofdifference between the “new” and the “newer” students

Not Important Very Important

Want to have prior course work, perhaps from foreigninstitutions, evaluated for domestic course equivalency andthen applied to domestic degree program requirements

Important Very Important

Ability to live in housing in the community more than incollege-owned or sponsored housing

Not Important Low Importance

Expect or seek the ability to enroll in on-line or other media-based courses to minimize commuting time, trips to campuses,and time to degree completion

Very important Very Important

A campus culture that permits students to quickly amasscredits that will lead to degree completion (Concerns for quickcompletion may trump concerns about learning; Credentialism, not learning, may be the more sought-aftervalue for this student group)


A teaching-learning system that utilizes computer-based andtelecommunications technology in classes or used to deliverclasses more conveniently available in distant locations


A setting where students and faculty members place high valueon academic honesty and integrity

Low Importance Not Important

An institution that accommodates varied religious traditions orcustoms

Low Importance Very Important

The institution has excellent “customer service” standards Important Very Important

Strategic Implications for “New” (NS-2) and “Newer” (NS-3) students

Administrators who are accustomed to having traditional students making up the majorityof the student population on their campuses are now faced with a multifaceted dilemma. Theirfuture environment includes:

‚ A diminished applicant pool from which traditional students can be drawn, formerlyan institution’s primary customer prospect;

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‚ An intense need to replace traditional students with others so that campus economicimperatives can be addressed; and

‚ A realization that the market from which replacements might be drawn is segmentedin ways that it has not been in the past (including a mix of NS-2 and NS-3 students).

We will examine the strategic implications of replacing traditional students in two categories:recruiting and service mix.

Recruiting

Universities have become very sophisticated at targeted recruiting. They will need tobecome even more so if they want to succeed in recruiting and enrolling students from the “new”(NS-2) and “newer” (NS-3) non-traditional student segments of the market to replace likely lossesfrom the “traditional” student cohort. For example, university Websites must become the centerpiece for recruiting because the newer non-traditional students (NS-3) use electronic sources as theirfirst point of contact, if not their only source of information. Other web-based strategies willencompass embellishments for the campus: Facebook and MySpace pages, You-tube promotions,and campus tours, including even virtual reality sites as places where potential newer non-traditionalstudents can be interested, informed, and, hopefully influenced.

Messages should also change to appeal to an older adult with more life experiences andresponsibilities. Many of the NS-3 students are aware of the educational programs available tothem, but have decided that the return on investment of their limited time and money does not justifyenrollment. Emphasis on convenience and receiving credit for life experiences will be importantto both the “new” and “newer” non-traditional student.

Strategies which target regional or local students as prospective enrollees will work forschools located in or near metropolitan areas. For schools not located in dense population areas,satellite learning centers may become necessary, which will also imply changes to the institutionsservice mix.

Service Mix

There are two key ideas for campus leaders to consider if they view NS-3 students asreplacements for the diminishing number of traditional students. First, the NS-3 students may notwant or need much of what institutions have traditionally included in their product/service mix(Dorm life, intercollegiate athletics, fraternities and sororities, co-curricular clubs, and other formsof campus life--like student government, drama and entertainment programming, fitness centers,etc.). Second, the NS-3 students may not be able to pay the prices that institutions have chargedtraditional students. Non-traditional students from either the NS-2 or the NS-3 cohorts may question

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why they should pay, in the form of tuition and fees, for so many campus attributes and/or servicesthat do not want or need but which heavily influence campus pricing models.

If these assumptions can be accepted as having some validity, then it follows that campusleaders need to re-think their concept of their product and of the aptness of the campus’product/services mix for this emerging segment of the higher education market. Leaders will haveto consider cost-cutting measures that will bring costs (and therefore tuition and fees) into line withwhat the customers from the non-traditional segment of the market would likely be willing and ableto pay.

Universities cannot assume that new, modern, or renovated on-campus living quarters willbe attractive to the NS-2 or NS-3 groups as both tend to work full or part-time, have other familyobligations, and general have little interest in on-campus activities or other aspects dormitory orcampus life. Learning and growth opportunities outside of the classroom, such as intercollegiateathletics, fraternities and sororities, co-curricular clubs, student government, drama andentertainment programming, and fitness centers have little attraction for the same reasons.

What does interest the NS-3 student is convenience, flexible programming and/or classscheduling, credit for life experiences, career-focused learning, career development and placementservices, and financial aid packages. Convenience includes access to necessary university resources:admissions, advising, registration, orientation, bill paying, libraries and computer labs, and parking.Flexible programming includes day, evening classes, and, perhaps, weekend classes. Credit for lifeexperiences suggests innovative ways to award credit to those who have been in the workforce andactually “doing” much of what they are scheduled to study. Most non-traditional students, becauseof family circumstances and responsibilities, seek ways to advance their careers as quickly aspossible. They have little time for classes that will not have an immediate benefit to them. For-profit universities exploit this need and have turned it into a billion dollar industry. Career focusmay also mean reconsideration of how subject matter is learned (Blaylock, et. al, 2009). Finally,financial aid can no longer be made available only to full-time students. Universities may have topartner with lending institutions and employers to create new loans and tuition assistance programsfor part-time students. Pricing differentials must also be considered because most non-traditionalstudents are not interested in or willing to pay for many of the extra-curricular activities or serviceson campus on campus. An example might be health centers. No one would argue that health centersare not worthwhile or important, but non-traditional students seldom use them, so, they reason, whyshould they be required to pay for them?

The critical reader by now has concluded many of the above changes can occur on campuseswith adoption of new technologies. Admissions are already done by many campuses on-line, oftenwith a consortium of other institutions. As broad-band access becomes more readily available anytype of interview can be done. Skype, Adobe Connect, and other conferencing technologies makemeeting online almost as effective as meeting face-to-face. Distance learning systems are nowpervasive in the for-profit education industry. Tier 2 – 4 schools have adopted such technologies

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as add-ons, but they may now need to become a central focus. Quality of such courses is alwaysimportant. Husson and Waterman (2002) have determined that selecting suitable faculty membersfor web-based delivery classes, providing them with training and support, carefully designing thelearning environment, providing students with technical and academic support, and developingpolicies to run the system are the most important characteristics for a successful distance learningprogram.

To return to the question posed at the beginning of this section, “Is it possible to recruit morenon-traditional students to make up for what the campus will likely lose as traditional studentschoose to go elsewhere, or if they choose to skip a traditional approach to earning a degreealtogether?” The answer is yes, but institutions will be successful only if they change their mindsetsabout the students who will be the majority on campus and about the very different needs they willhave. This is nothing short of a cultural change. A metamorphosis of this type may be lengthy andit may require turning loose of old traditions, but it will be an essential step for many schools whosesurvival will be “on the line.”

THEME THREE: ECONOMICS

Campus Development

Strategic and long-range planning has become a central part of leadership on collegecampuses. Leaders must actively position their institutions within ever changing marketplaces bycreating institutional environments designed to meet the needs and desires of future students.Planning goes beyond creating new programs or revamping current ones. It also entails infra-structure, support services, and program delivery options. Critical to any strategic plan are theassumptions upon which the plan is built.

Some universities and colleges seem to cling to assumptions true in the past, but which maybe questionable now. Among these are

1) More students, just like those served in the past, would be drawn to newly-enlarged and modernized campus,

2) Students would expect services and facilities to be as good as or better thanthose demanded in the past,

3) Tuition can be increased on an average of 5% per year into the indefinitefuture, and

4) Though possibly difficult, it is always possible to increase market share; butmaintaining market share will be “no problem,” and losing market share isnot a plausible future outcome.

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Colleges and universities across the country (See Himmelspach, 2008; University ofAlabama at Birmingham, 2007; Harvey Mudd College, 2007; University of Kansas, 2007;University of Wisconsin, 2007) have been engaged in extensive projects to create new and/orrenovate old facilities. It would seem that they have adopted the philosophy of “If you build it, theywill come.” One is tempted to conclude that planners on these campuses, as they have investedheavily in major traditional bricks and mortar projects, have failed to notice the significant presenceand success of on-line and virtual universities, or that planners have not perceived these programsas a market threat to their own institutions. One is further tempted to conclude that demographicchanges, that clearly will affect the number and type of future students that will come to theircampuses, were not perceived as relevant. Are some of these institutions headed toward committinga major error by erecting an ever-larger or ever improved physical plant? Even if gift and grantincome could be obtained to fund many of the planned improvements, there are recurring costs (forutilities, maintenance, repairs, and maintenance staff) that could cause wonderful new teaching andlearning spaces to become a financial albatrosses around the neck of any institution where projectedincreases in enrollment fail to materialize, or where enrollments actually decline.

Strategic Implications of Campus Development

Making decisions about the location and type of physical facilities needed to support collegeand university programs are, from the point of view of strategic planning, among the mostsignificant decisions that academic leaders ever make. Apart from cost, facilities decisions arestrategically important because they must support and be congruent with the institutional mission.If an institution has ambitions to grow, change, or improve, such aims have implications for thefacilities and other resource requirements.

As higher education has evolved, and as new providers have entered markets, newapproaches have emerged for providing physical facilities to support educational programming.Traditional institutions with long histories in their communities were developed under a model thatincludes elaborate and spacious grounds, punctuated with many specialized buildings, served by anextensive support staff, and accompanied by an expectation that students come great distances topartake of academic options offered. Consider such places as “Model 18” campuses—given thatthe model was developed in the 18th Century in the U.S. Campuses developed under this modelwere, and still are, very “place bound” which makes it difficult for institutions to respond tochanging demographics that affect demand. Significantly, the Model 18 campus also carries withit substantial overhead costs that must be factored into institutional pricing strategies. This aspectcan be problematical—irrespective of challenges an institution might face when demographicschange.

Newer entries in higher education have entered markets with an entirely different physicalfacilities model. Think about institutions like the University of Phoenix, Argosy University, and

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DeVry University/Keller Graduate School of Business as the exemplars of the newer entries thathave seized upon a different approach to campus design. Having settled on a somewhatstandardized design model, the newer entries have replicated the model in many cities across thecountry. We refer to these newer campuses as “Model 21” campuses—given that this concept ofcampus design emerged in the 21st Century in the U.S. The Model 21 campus design embeds valuejudgments that developers have made about what things are important to NS-3 students. A Model21 approach has often been used, to a degree, by Model 18 campuses when such institutions havesought to expand their scope by offering courses in distant settings. Table 3 illustrates contrasts theelements of the newer (Model 21) campus facilities model with those of the traditional (Model 18)campus facilities model.

Table 3 Comparing the Physical Facility Attributes of Traditional College Campuses with an EmergingModel of New Campus Development

Facility Attribute “Model 21” - Newer CampusModels

“Model 18” - TraditionalCampus Model

Comment

Ownership

Modest, leased space in officebuildings

Extensive, buildings andgrounds owned by theinstitution Model 21 allowseasy entry and exits into andout of markets

Reason for LocationChoice

Site selection driven by anassessment of market potential

Site selection driven by anhistorical assessment ofmarket; political and otherfactors

Model 18 campuses cannoteasily adapt to changingdemographics

TransportationConsiderations

Critical site selection criteriaare proximity to arterial roadsand public transportationand/or ample parking

Transportation issues werenot usually considered. Theciting of many campuses pre-dated modern road systemdevelopments

Model 18 campuses mayoriginally been located nearheavy rail stations

Who Staffs?

Staffed by a Center Directorand a small number of supportstaff who may be part-timeemployees

Staffed by extensive numberof administrators and supportstaff members

Library/LearningResources

“Library” may be a room witha few computer terminals foron-line searches and a limitednumber of periodicals andreference works; little or nostaff support

Extensive resources andmany full time staff membersto offer service

In Model 21 schools,students are told to usecommunity libraries andlibraries of other higherlearning entities, thusshifting an institutional costto others

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Table 3 Comparing the Physical Facility Attributes of Traditional College Campuses with an EmergingModel of New Campus Development

Facility Attribute “Model 21” - Newer CampusModels

“Model 18” - TraditionalCampus Model

Comment


Computer Utilities

Computer utility may be aroom with a small number ofcomputers

Extensive computer utilityand staff to support it

In the new model, studentsare expected to have theirown access to computersand connectivity at home orat work

Food Service

Vending machines providedunder contract with outsidesupplier

Extensive food serviceoperation offering food inmultiple campus sites. Institution staff or outsidevendor may provide theservice

Offering high quality foodservice was once, and stillis, an importantcompetitive feature onModel 18 campuses

PhysicalEducation/Health &WellnessOpportunities

None provided Extensive facilities and fulltime staff provide theseopportunities

MaintenanceProvided by lessor or providedby lessee under contract withoutside firm

Provided by an extensivemaintenance staff on theinstitution’s payroll

Security If provided—offered by part-time contract personnel

Extensive staff of full timecampus security officers

Faculty

Predominantly part-time,independent contractors

Mix of full time employeesand part-time, independentcontractors, and teachingassistants

Though diminished as apercentage of the totalfaculty, full-time, and oftentenured, faculty memberswere the pride, and a majorselling point, of Model 18campuses

Marketing Slant

“The institution is where youare! It’s convenient andclose.”

“Come to where we are andbask in the beauty andtradition of our campus.”Model 21 institutions adoptthe “Marketing Concept”;Model 18 institutions arepursuing the “ProductionConcept.”

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Leaders on many campuses should use caution with respect moving ahead with campusdevelopment plans—especially if and where they involve significant commitments to infrastructureand brick and mortar projects. The arguments in favor of exercising caution include the following:

‚ Projected decline in the pool of “traditional students,” reported above suggests thatcollege and universities farther down on the “Perception of Quality Scale” (Table1) will be those that lose the largest number of students from that group. This will,of course, imperil the financial conditions on such campuses.

‚ College leaders, most especially those heading up Tier 3 and Tier 4 institutions, ina quest for institutional viability, will need to vigorously, recruit students in the NS-3cohort to replace any traditional students that will be lost, most likely, to Tier 2schools.

‚ If the NS-3 students recruited to replace lost traditional student enrollments on acampus cannot afford to pay the costs of their education in the same manner as didtraditional students; or as did the NS-2 cohort, a college will most likely have todiscount tuition more aggressively than usual to get the NS-3 students to enroll.Thus, in a situation where an institution was able to replace 200 lost traditionalstudents with 200 NS-3 non-traditional students, discounting would reduce grossrevenues; and per student profit margins will decline. The financial problem will beexacerbated if the 200 NS-3 students need extra services (such as more tutoringassistance in basic language skills) that would boost the expense side of the ledger.As can be seen, the loss of one traditional student will have to be made up for byrecruiting more than one NS-2 or NS-3 student in order to get an institution in astate of financial equilibrium.

‚ If the NS-3 cohort is not buying what traditional colleges are selling, then campusleaders should think twice before building, creating, or offering more of the “sameold thing” going forward into a changing higher education market place. It isimperative that campus strategic planners discern contemporary student needs anddemands or else they will fail to develop facilities, services, programs, or otherinitiatives that will have high probabilities for success, financial or otherwise.

‚ The growth and success trajectory of on-line and more career-focused, for-profitinstitutions of higher learning strongly suggests that such institutions are going tocontinue to make in-roads into the market shares of traditional colleges anduniversities. More traditional colleges and universities, especially, those operatingat the margins of higher education, must create strategies to fend off those incursionson their market share if they seek to survive going forward.

‚ Student interest in alternative schedules, in the ability to take on-line courses, andin taking instruction at distance learning facilities should be factored into atraditional college’s future strategic plans even if these modalities have not been

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emphasized in the past. Institutions considering more traditional bricks and mortarexpansions should pay special attention to the increased likelihood that thesestructures, representing part of their service mix strategies, may not be as successfulas history suggests.

Increase in Higher Education Cost

Meeting the demands of a changing market by adding or adjusting product/service offeringsis a costly proposition in most industries. This is true for higher education institutions as well. Likeproduct/service mix changes made by private sector organizations, improvements to college anduniversity campuses are costly too. On the typical campus, revenue comes from only four sources:1) tuition and fee income; 2) sales from auxiliary services such as food service, housing, facilitiesrentals, and bookstore operations; 3) grant and contract income; and 4) donations and non-monetarygifts. Of the four sources, tuition and fee income is the most important on any campus.

An examination of recent institutional behavior seems to suggest that most college anduniversity leaders are assuming that they can upwardly adjust their tuition and fees over the yearsto cover the increased costs of providing a more attractive value proposition for traditional students.From the 1996-97 to 2006-07 school years, tuition and fees at private four-year institutions increased82.8% and 96% at public four-year schools (U.S. Department of Education, 2008). During that sameperiod, the Consumer Price Index has increased 56.2% (InflationData.com, 2009). In other words,a belief exists on many campuses that there is no point at which consumers will say “no” to tuitionand/or fee schedules. Apparently, college and university leaders don’t believe that they can pricethemselves out of the market. Wrongly, they assume that the demand for higher education isinelastic. That is to say, students will continue to enroll in a college no matter how high tuition andfee charges ascend. In truth, demand for higher education may be very elastic. This leads to theinevitable conclusion that a high cost structure looms as a serious potential problem on manycampuses.

An analogy can be made between the attitudes of many college leaders and the attitudes ofmany in the real estate industry. The mortgage market melt-down of 2008-2009 proved housingprices would not increase indefinitely going into the future. The correlated crisis in the financialsystem has brought additional, unwelcome changes in many sectors of society—including areorientation of student and parent decision-making about spending money on college tuition.Black, writing in the Chicago Tribune (2009), reports that students who have applied for and gottenacceptance notices from elite schools are opting to enroll in less-prestigious schools for financialreasons. “Even as the amount of tuition loans rises, students deciding on colleges are increasinglyweighing finances as a major factor, forcing many to opt for their second or third choice.” Otherstudents, who normally would have aimed to enroll in more selective, or more prestigious privateinstitutions, have shifted their focus toward the less-costly public universities. One observer noted

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that “…we have seen 60-65 percent of students applying to public universities…whereas, a year ago,it was just the inverse.”

Strategic Impact of Increased Higher Education Costs

The extant and emergent stresses in the economy and in the financial markets during 2008-2009, and its likely extension into 2010, will surely test the elasticity/in-elasticity of demandargument with respect to high education. Campus leaders are encouraged to pay attention to theresults of that test. What is the writers’ guess? First, it is likely that campus financial conditionswill get worse before they get better—especially among institutions that, historically, have beenpublicly-funded (i.e., the “state schools”). Until the millennium approached, higher education had,for decades, been the “favored child” of state legislatures; and funding from the legislatures flowedinto state schools in predictable and generous ways. However, from about the early 1990s onward,competing social priorities began to eclipse higher education as the areas where public dollars werethought to be most need (Kane, Orszag, & Gunter, 2003). More often than not, expanded socialservices, public safety improvements (including prison expansions), health care improvements,environmental concerns, early childhood education, and other issues have been considered moreworthy of funding than was pouring more funds into the coffers on the ivied college and universitycampuses. As a result of this shift in legislative emphasis, campus administrators had no riper placeto turn, as they looked for revenue to replace diminishing state support dollars, than to tuition andfee structures. Tuition and fees have increased at a much higher rate than has inflation or statebudgets (U.S. Department of Education, 2008). On some campuses, increases have been steady butmore moderate. It is likely that this trend will continue wherein students and/or their parents (andnot the state) will be expected to carry more and more of the cost burden for a student attending astate school (Kane & Orszag, 2003; Archibald & Feldman, 2006). The private universities havebeen just as prone to increasing tuition as have the public schools, but they have sought to mitigatethe increases to a degree by being both more aggressive and sophisticated than the public schoolleaders in seeking private support from alumni and other donors.

Second, it is also likely that in response to ever-increasing tuition and fees, students (andtheir parents, employers, or whomever subsidizes students’ school attendance) will begin to rebelagainst these rising tuition and fee charges. The rebellion will likely be fueled by cost-benefitanalyses that could reveal that the projected income from jobs that might be assured to those whoearn college degrees may not be high enough to justify the increasing expense of earning thosedegrees (Fish, 2009). If the projected rebellion does occur, it should be greatest among students whomight normally pursue degrees in the social sciences, education, and fine arts and the humanitieswhere salary incomes are lower than in business, medicine, law, engineering, and the hard sciences.

Third, rejection of the college degree as “preparation for the world of work” of work mightbe abetted by further disintegration of the domestic economy. When domestic job creation slows,

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when unemployment rises, and when so many domestic jobs are out-sourced off-shore, a predictableadverse effect upon the perceived benefits of earning a college degree will become a matter of fact(Lyall & Sell, 2005; Fish, 2009).

Ip (July 2008) recently commented on this topic when he observed that “A four-year collegedegree, seen for generations as a ticket to a better life is no longer enough to guarantee a steadilyrising paycheck…For decades the typical college graduate’s wage rose well above inflation. But,no longer! In the economic expansion that began in 200l and now appears to be ending, theinflation-adjusted wages of the majority of U.S. workers didn’t grow, even among those who wentto college…College-educated workers are more plentiful, more commoditized and more subject tothe downsizings that used to be the purview of blue-collar workers only (Ip, July 2008).” Ipcontinues on by writing that workers today need to understand “… how insecure any job can be andhow little a college degree by itself stands for…Employers are going to ask ‘What else have youdone in your life besides going to college?’”

As these realities begin to “sink in” with prospective students, it is quite logical to believethat the appeal of traditional degree programs will decline, especially at institutions wheretraditional degree programs are delivered in traditional locations, in traditional formats, and withtraditional methods of instruction. At the very least, it is likely that when prospective studentsconsider their options, a shift in student preferences will occur—away from four-year college anduniversity programs and toward lower cost, shorter-term, career-focused programs, like thoseoffered in community colleges. Other beneficiaries of a shift could be the for-profit, career-focusedtwo- and four-year colleges. Tuition is not cheap in such schools, but they operate in ways that tendto compress the experience and minimize “time to degree” (and, therefore, minimize both out-of-pocket and opportunity costs for students). That is certainly a marketing advantage whenconsumers are price-sensitive. Those career-focused institutions also tend to do a better job inconcurrently providing both distilled theoretical knowledge and hands-on training to their students.As noted, this combination is one that employers increasingly favor.

Finally, while elite colleges and universities will always have enough cachet to draw studentsirrespective of cost, many “down-market” schools don’t, and won’t ever share that lofty position inthe pantheon of higher education institutions. Those colleges and universities in the lower tiers onthe academic quality perception scale face a significant competitive challenge on many fronts thatwill influence their ability to do well—or maybe even their ability to survive—in the highereducation market place in the years that lie ahead. If these same institutions, in addition to theirother competitive challenges, persist with ever-increasing tuition and fee structures, they will surelydrive themselves out of the market for students. They will especially drive themselves out of themarket made up of the diminishing pool of traditional students.

About a decade ago, Levine (1998) observed that “…this is also a time of danger. It is notclear that higher education as it has evolved to the present day can survive unchanged into the future.Its present design and structure may not be sustained. It faces a radically different environment than

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in the past…” We not only think that it remains a time of danger, but that the danger has increasedbecause the environment is even more hostile than when Levine wrote those words. Previouslyvenerable and admired institutions that fail to adjust their strategies to the realities of thecontemporary higher education marketplace will be more vulnerable than ever before.

CONCLUSION

Shifting demographics, changing student attitudes and expectations, volatile economicconsiderations, galloping advances in technology, globalization, and increased competition withinthe higher education market place present significant, on-going challenges to college campus leaderswho are responsible for charting the strategic directions for the future of the institutions which theylead.

Successfully coping with these changes requires campus leaders to engage in what Fullan(2001) calls “reculturing.” Stop for a moment and think about how foreign the following tacticaland implementation steps are within the academic strategies followed by a very large number of verytraditional U.S. colleges and universities: highly career-focused curricula; tele-courses, internet/on-line courses and degrees, and other forms of non-face-to-face; credit-for-life experience programs;service learning experiences; off-site courses and degree programs in distance learning centers andemployer workplaces; differential tuition pricing; inter-institutional collaboratives, etc. These andany number of other contemporary methods for delivering instruction, providing services, andotherwise working with students are hardly the sacrosanct and hallowed practices within mosttraditional institutions that currently work in the higher education market space. Yet, it is exactlythat type of reculturing which is needed on many traditional college campuses to better strategicallyposition themselves to compete in the marketplace for the kind of students who will be available andinterested in pursing a degree. The strategic re-positioning would involve the adoption of many ofthe marketing, pricing, delivery methods and student services that have been mentioned in thispaper.

Strategic approaches to responding to the projected declines in traditional studentpopulations will yield opportunities for institutional survival and success, but only if academicleaders can release many of their fond and happy thoughts about the old alma mater that are, inreality, constraints.

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JOB ORDER COSTING: A SIMULATION ANDVEHICLE FOR CONCEPTUAL DISCUSSION

Rochelle K. Greenberg, Florida State UniversityArnold Schneider, Georgia Institute of Technology

ABSTRACT

This paper offers a hands-on approach to teaching job order costing in introductorymanagerial accounting or in cost accounting. It is motivated by the belief that students would havea better appreciation of how goods and costs flow in a manufacturing firm through an experientiallearning exercise as opposed to passive learning methods such as reading a text description orlistening to a lecture. The exercise involves the simulated manufacture of a table from the purchaseof raw materials through the sale of the finished product. Cost accumulation is illustrated usingboth actual and normal costing systems.

INTRODUCTION

Job order costing is typically covered in cost accounting and managerial accounting coursesand appears in virtually all such textbooks (e.g., Hilton, 2005; Schneider, 2009). Students often havedifficulty understanding job order costing because they do not have a good understanding ofmanufacturing processes. To overcome this lack of understanding, it would help for students to beexposed to an actual manufacturing operation. The exercise described in this paper allows thestudent to experience a manufacturing operation in the classroom. The exercise involves themanufacture of a custom-made table out of balsa wood and other materials. The process begins withthe purchase of raw materials and ends with the sale of the finished product.

Although other approaches have used LEGO® blocks to teach management accounting termsand techniques (Roth, 2005; Morgan, Martin, Howard, & Mihalek, 2005; Burns & Mills, 1997), thissimulation is different in two major ways: (1) it focuses solely and comprehensively on job ordercosting whereas previous articles have only superficially covered job order costing, and (2) by usingthe variety of materials called for in this simulation, the product and manufacturing process is morerealistic, affording the students the ability to clearly see the differences between direct materials andindirect materials, direct labor and indirect labor, and other items that constitute manufacturingoverhead. We feel that this is an extremely important differentiation not only in understandingtraditional cost accounting, but in understanding activity-based costing, since the difference betweenthe two methods lies with overhead. This method of teaching job order costing provides the student

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with a hands-on experience and allows them to actively participate in the learning process. It issuitable for practically any classroom configuration with any number of students.

Two methods for increasing student interest discussed in the literature involve making theinstruction fun and hands-on (Davis, 1993). The simulation described in this paper accomplishesboth of those objectives. When students are interested in the topic, they are more likely to rememberthe lessons and key points (McKeachie, 1994). Simulations and role-play can be particularlyeffective teaching techniques by arousing interest, providing a concrete basis for discussion, and byillustrating the major principles from the lesson. Studies have shown active learning techniques suchas simulations and role-play to be stronger than traditional methods of instruction in terms ofknowledge retention, knowledge application, and motivational outcomes (Dekkers & Donatti 1981;McKeachie, 1999).

We have used this manufacturing simulation in undergraduate managerial and costaccounting classes, and in an MBA class to teach job order costing. The exercise reinforces cost andother concepts, such as types of costs and types of inventories, to which the students have beenbriefly exposed prior to learning about job order costing. The primary purpose of our exercise,however, is that it demonstrates how products flow through the factory and how the correspondingcosts of making the product flow through the accounting system. The student sees first-hand howcosts are accumulated and product cost is determined in a job order cost system. The exerciseillustrates the use of source documents unique to job order costing such as the job cost sheet, timetickets, and materials requisition forms. The unique issues associated with how to chargemanufacturing overhead to a particular job are also discussed, along with the procedures andconcepts of an actual cost system versus a normal cost system.

OVERVIEW AND PURPOSES OF EXERCISE

We illustrate the flow of goods and costs in a manufacturing firm using a job order costsystem by simulating a manufacturer of custom-made furniture. During a specified time period, wehave a company working on three different pieces of furniture – table, bookshelves, and chinacabinet. For simplicity, we fully demonstrate only the manufacture of the table. The process beginswith the purchase of materials from a supplier and ends with the sale of the completed table to acustomer. After the student has an understanding of the physical flow of the product through thefactory and the corresponding flow of costs through the manufacturing accounts, the bookshelvesand china cabinet are introduced through their already updated job-cost sheets. At the end of theperiod, it is assumed that the bookshelves are completed and in finished goods, and that the chinacabinet remains in work in process inventory.

The simulation is divided into two parts; Part I illustrates the flow of the product through themanufacturing facility and the corresponding flow of costs through the accounting system, whilePart II involves allocating manufacturing overhead to the job. Both an actual cost system and a

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normal cost system are illustrated. Many different teaching opportunities present themselvesthroughout the simulation and are noted in our discussions.

The purposes of the exercise are:

‚ To demonstrate how products flow through the factory. ‚ To demonstrate how the cost of making the product flows through the accounting

system in a way that mirrors the physical flow of the goods through the factory. ‚ To demonstrate how manufacturing costs are accumulated and how unit cost is

determined in a job order cost system.‚ To demonstrate how manufacturing overhead is allocated; the unique issues

associated with allocating overhead and how it is allocated in an actual cost systemand in a normal cost system.

‚ To set the stage for a discussion of activity-based costing and comparison oftraditional and ABC product costs.

‚ To actively engage the students, help form community in the classroom, and to makeaccounting fun.

METHODOLOGICAL APPROACH

The instructor will need to provide the following supplies for the exercise:

‚ Miniature bookshelves* to use as a prop in the finished goods (FG) inventorywarehouse;

‚ Miniature china cabinet* (in incomplete form) to use as a prop in work in process(WIP) inventory;

‚ One piece (3/32” x 6” x 36”) of balsa wood to serve as oak wood for a table baseand legs [direct materials (DM)];

‚ One clear plastic sheet (8.5” x 11”) protector (trimmed and separated) to serve asa glass top for the table [DM];

‚ One piece of non-adhesive felt (9” x 12”) to protect the glass from the wood base[indirect materials (IM)];

‚ Glue [IM] to adhere the felt pads to the corners of the wood base;‚ One small container of brown paste shoe polish for stain [IM];‚ One piece of sandpaper [IM];‚ One paper towel to rub stain on the table [IM];‚ Ruler for measuring;‚ Pencil for marking measurements;‚ Cutting board;

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‚ Knife and/or scissors to cut plastic paper sheet protector, felt, and wood (make surethat the knife/scissors is strong enough to accommodate the thickness of the wood);

‚ Masking tape to mark off the departments: Raw Materials (RM) Warehouse, twomanufacturing departments – Cutting and Finishing, FG Warehouse. Masking tapemay not be necessary if the classroom can be logically divided in another way. Forexample, we have used chairs to serve as the RM Warehouse and the FG Warehouse,and a table to serve as the manufacturing floor.

‚ * Miniature furniture may be purchased at a hobby store.

We chose these particular materials to get a good mixture of direct materials and indirectmaterials. We use two examples of direct materials, and use indirect materials that are incorporatedin the finished product (i.e., felt pads, glue, stain), as well as indirect materials that do not becomepart of the product (i.e., sandpaper, paper towel).

The instructor will need to select six students for the following roles:

‚ One deliverer of the raw materials from an outside supplier‚ One RM Warehouse Storekeeper‚ Two direct labor (DL) workers:

--Cutting Department DL worker (DL worker A)--Finishing Department DL worker (DL worker B)

‚ One FG Warehouse Supervisor‚ One customer

The instructor can act as the Production Supervisor as well as the Cost Accountant. Eachof the students wears an 8.5” x 11” sign with their job title around their necks.

It is helpful to display a prototype of the table so the students have a visual of what they aretrying to make. Also, in the interest of time, mention to the students that the table need not be madeto perfection.

Students should be provided with the following five handouts:

‚ “The Flow of Product Costs in a Manufacturing Company” (see Figure 1);‚ “T-accounts for Assume Table is Finished and Sold” (see Figure 2);‚ “Time Tickets & Materials Requisition Form” (see Figure 3);‚ “Job Cost Sheets for Jobs #1, #2, and #3” (see Figure 4);‚ “T-accounts for Assume Table is Finished and Sold, Bookshelves are Finished, and

China Cabinet is Not Finished” (see Figure 5).

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MANUFACTURING PROCESS

The manufacturing facility encompasses the raw materials and finished goods warehouses,and the factory floor, where production takes place. The factory floor consists of two differentmanufacturing departments, the Cutting Department and the Finishing Department. A descriptionof the factory floor follows:

Sales to customers | | RM Inv. Warehouse WIP (Cutting Dept.) WIP (Finishing Dept.) FG Inv. Warehouse | | Purchases from outside vendors

When purchased, raw materials are delivered to the Raw Materials Inventory Warehousewhere they are stored until requisitioned for production. When requisitioned, raw materials aremoved out onto the factory floor where actual production takes place; all materials there areconsidered work-in-process until production is completed. In the Cutting Department and in theFinishing Department, factory employees combine materials with their labor to produce finishedproducts. The finished products are then moved into the finished goods inventory warehouse andstored until sold.

PART I

Part I of the simulation illustrates the flow of the product through the factory and thecorresponding flow of manufacturing costs through the accounting system.

Teaching opportunity: Discuss the basics of a job order cost system and why it isbeing used in this particular manufacturing operation, as opposed to a process costsystem.

The exercise commences with the following procedures:

Set up the classroom by designating space for the RM Warehouse, the factory floorcontaining two distinct departments for WIP (Cutting and Finishing), and the FGWarehouse.

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Briefly review “The Flow of Product Costs in a Manufacturing Company” handout(see Figure 1), which presents the account entries needed throughout themanufacturing process from the purchase of raw materials to the sale of theproducts.

Figure 1 -- The Flow of Product Costs in a Manufacturing Company

DL worked CGS

Purchases of RM

Beg Bal

--

+

+

+

+ +

Raw Materials

Wages Payable

WIP Finished Goods CGS

Manufacturing Overhead

+

-

-

-

-

Used

Ending Bal.

Ending Bal. Ending Bal. Ending Bal.

(Labor wages paid)

Labor worked CGS

when sold- Beg. Bal

Cost of Goods Manufactured

when completed-

Cost of Goods Manufactured

Beg. Bal. DM Used

Applied O/H

Applied O/H

Actual O/H indirect materials used indirect labor worked other actual O/H

Over/Under-applied O/H

The “T-accounts for Assume Table is Finished and Sold” handout (see Figure 2)should be copied on the board or placed on an overhead projector so thatthroughout the manufacture of the table, the instructor can demonstrate how themovement of the product costs through the accounting records mirrors the movementof the product through the factory. All T-accounts will have $0 beginning balances.

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Figure 2 -- T-accounts for Assume Table is Finished and Sold

Manuf Overhead

Finished Goods

Actual Applied

+

Wages Payable

- + WIP

- + CGS

+ - -

Raw- +

At this time, the instructor begins to walk the students through the transactions andtransitions that encompass the manufacturing process. The first transaction involves the purchaseof raw materials. When purchased, raw materials (both direct materials and indirect materials) aredelivered to the raw materials inventory warehouse where they are stored until taken out forproduction. Assume the company purchases $4,000 of raw materials and places all direct andindirect materials (wood, glass, stain, felt, etc.) in the RM Warehouse. The instructor updates theRaw Materials T-account on the board by adding $4,000 for the purchase from outside suppliers.

Next, the instructor explains the direct labor costs which involve two workers – one in theCutting Department and the other in the Finishing Department. The job of DL worker A (CuttingDepartment) is to cut the wood and glass (i.e., sheet protector) for the table. DL worker A fills inhis time ticket (see Figure 3), indicating he is starting work at 8:00 AM on Job #1. See Time Ticket#1 below.

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Figure 3 -- Time Tickets & Materials Requisition Form

Time Ticket #1 Employee _____________________ Date ________________ Started Ended Time Completed Rate Amount Job Number Supervisor ____________________________ ---------------------------------------------------------------------------------------------------------------------

Time Ticket #2 Employee _____________________ Date ________________ Started Ended Time Completed Rate Amount Job Number Supervisor ____________________________ ---------------------------------------------------------------------------------------------------------------------

Materials Requisition Form Job Number to Be Charged ______________ Date ___________________ Department _______________ Description Quantity Unit Cost Total Cost

Teaching opportunity: Explanation of a time ticket.

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Time Ticket #1 Employee: Student’s Name Date _______ Started Ended Time Completed Rate Amount Job Number 8:00AM 1 (Table) Supervisor: Instructor’s signature

DL worker A then requests the materials (i.e., wood and glass) needed to begin work on thetable – Job #1.

Teaching opportunity: Explain the difference between DM and IM.

The wood and glass are DM and are economically worth tracing. Accordingly, DL workerA fills out a Materials Requisition Form (see Figure 3), asking for wood and glass, and presents itto the RM Warehouse Storekeeper.

Teaching opportunity: Explanation of a Materials Requisition Form.

The completed Materials Requisition Form appears below:

Materials Requisition Form Job Number to be Charged 1 Date _______ Department Cutting Description Quantity Unit Cost Total Cost oak wood 48 sq. inches (one 6” x 8”board) $3.00/sq. in. $144.00 3/8” glass 80 sq. inches (one 8” x 10” glass) $ .70/sq. in. 56.00 $200.00 Authorized Signature Instructor’s signature

The Storekeeper gives DL worker A the requested materials and sends the MaterialsRequisition Form to the Cost Accounting Department. The Cost Accounting Department (i.e., theinstructor) completes the cost information on the form (i.e., unit costs and total costs), and beginsto keep track of the entire job’s costs via a Job Cost Sheet (see Figure 4 for the Job Cost Sheets).The DM cost is entered on the Job Cost Sheet upon receipt of the Materials Requisition Form for

48


that specific job. For the table, Job #1, the total DM cost entered is $200. In addition, the instructorupdates the T-accounts on the board, moving $200 out of the RM Inventory account and into theWIP T-account. Once on the factory floor, all materials are considered WIP until the process iscompleted.

Figure 4 -- JOB COST SHEETS FOR JOBS #1, #2, and #3

JOB #1 JOB #2 JOB #3 Table Bookshelves China Cabinet Job Cost Sheet Job Cost Sheet Job Cost Sheet TOTAL DM $200 DM $700 DM $2,000 DM DL 75 (5hrs.@ $15) DL 150 (10hrs.@ $15) DL 525 (35hrs.@ $15) DL O/H O/H O/H O/H Total Cost Total Cost Total Cost Total Cost

Teaching opportunity: Explanation of a Job Cost Sheet.

Next, DL worker A cuts the table, cuts the legs, and cuts the glass to the specified sizes. DLworker A begins making the table by cutting the wood to measure 6” wide and 8” long. Then, thestudent pokes a hole in the middle of the wood and cuts out a 2” wide and 4” long piece so that thestudent is left with a 2” frame that will serve as the base for the glass top. Using the 2” wide and4” long piece, the student cuts four legs, each one approximately 4” long and 1/2” wide. Finally,DL worker A cuts the glass so that it measures 8’’ wide x 10” long.

We assume that DL worker A works on the table for three hours (5 - 10 minutes real time),and then sends the table to the Finishing Department. DL worker A updates the time ticket toindicate the time spent working on Job #1 (i.e., until 11:00 AM) and sends the time ticket to the CostAccounting Department. The instructor finishes filling out Time Ticket #1, charging the time to Job#1, as follows: Time Ticket #1 Employee Student’s Name Date _______ Started Ended Time Completed Rate Amount Job Number 8:00AM 11:00 AM 3 hours $15.00 $45.00 1 Cuts wood and glass. Supervisor Instructor’s signature

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Using Time Ticket #1, the Cost Accounting Department updates the Job Cost Sheet for Job#1 with $45 DL, and the instructor accordingly updates the T-accounts on the board, increasingWages Payable and increasing WIP by $45. The instructor may wish to emphasize that the DL costsbecome part of WIP, rather than being treated as wages expense.

Once the cutting portion of the job is complete, the job moves to the Finishing Department.There, the job of DL worker B is to stain and assemble the table. First, the student stains the woodframe and the four legs. The legs are then attached to the frame by inserting them into thin slits thatthe student cuts in each corner of the table frame. Finally, the student cuts the felt into four ½”square pieces and glues each piece to the outside corners of the wooden frame. The glass is thenplaced on top of the 2” wood frame and the table is complete! DL worker B fills in his time ticket,Time Ticket #2, to indicate he is beginning work on the table (Job #1) at 11:00 AM, as follows:

Time Ticket #2 Employee Student’s Name Date ________ Started Ended Time Completed Rate Amount Job Number 11:00AM 1 Supervisor: Instructor’s signature

DL worker B commences his work by obtaining the (indirect) materials required to assembleand stain the table (i.e., sandpaper, stain, paper towel, felt, and glue).

Teaching opportunity: Discuss the differences between direct materials and indirectmaterials and how they are handled in the costing of the product. Note there is nomaterials requisition form required in the Finishing Department because of the costsof charging such immaterial amounts to the specific job compared to the benefitsthat would be achieved by doing so.

Assume that DL worker B works on the table for two hours (5 minutes real time). He stainsthe table, assembles it, puts on the felt pads, glass, etc., and takes the table to the Finished GoodsWarehouse Supervisor. DL worker B updates his time ticket to reflect time worked from 11:00 –1:00 on Job #1 and sends the time ticket to the Cost Accounting Department. The completed timeticket appears below:

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Time Ticket #2 Employee: Student’s name Date _______ Started Ended Time Completed Rate Amount Job Number 11:00AM 1:00 PM 2 hours $15.00 $30.00 1 Stains and assembles the table. Supervisor: Instructor’s signature

The Cost Accounting Department updates the Job Cost Sheet for Job #1 with $30 DL, andthe instructor accordingly updates the T-accounts on the board, increasing Wages Payable andincreasing WIP for $30.

To finish costing the job, we need to charge it with manufacturing overhead. The techniquesfor allocating manufacturing overhead to the job are discussed in detail in Part II of the simulation.For now, the Cost Accounting Department should charge the job with $125.00 of overhead (this willbe the applied overhead amount using a predetermined overhead rate, as will be shown in Part II).The instructor updates the T-accounts on the board, crediting the manufacturing overhead accountand charging WIP with $125 of overhead. At this point, the Production Supervisor (i.e., theinstructor) informs the class that Job #1 has been completed and is being transferred from WIP toFG.

The Finished Goods Warehouse Supervisor lets the Cost Accounting Department know thatJob #1 has been transferred in. Cost Accounting will then close out the Job Cost Sheet for Job #1,and the instructor accordingly updates the T-accounts on the board, transferring the costs of the table($400) from WIP to FG. The instructor should point out that the $400 cost of the table results from$200 of DM, $45 of Cutting Department DL, $30 of Finishing Department DL, and $125 ofmanufacturing overhead.

Assume that the table is sold on account to a customer for $750. The customer (i.e., student)takes the table and returns to his seat. The instructor updates the FG and Cost of Goods Sold (CGS)T-accounts, transferring $400 from FG to CGS, and then also recognizes $750 of accountsreceivable together with $750 of sales revenue.

The bookshelves and china cabinet are now introduced through their already updated job-cost sheets. Refer to Job Cost Sheet handout (Figure 4), where dollar amounts for DL and DM havealready been charged to the jobs. At the end of the period, it is assumed that the bookshelves arecompleted and in finished goods, while the china cabinet remains in WIP inventory. Further, weassume that Job #2 (the bookshelves) has been charged with $250 of manufacturing overhead andJob #3 (the china cabinet) has been charged with $875 of manufacturing overhead. The job cost

51


sheets for all three of the jobs can now be completed. At this time, the instructor resets the room,placing the china cabinet in the WIP area and the bookshelves in the FG area (the table is no longerin the factory).

Using the data from the completed Job Cost Sheets, fill in the blank T-accounts on Figure5, which assumes that the table is finished and sold, the bookshelves are finished, and the chinacabinet is not finished. The WIP T-account should have an ending balance of $3,400, reflecting allcharges to the china cabinet; the FG inventory should have an ending balance of $1,100, reflectingall charges to the bookshelves; the CGS T-account should have a balance of $400, reflecting the totalcost of the table.

Figure 5 -- T-accounts for Assume Table is Finished and Sold, Bookshelves are Finished,and China Cabinet is Not Finished

Manuf. Overhead

Actual Applied

Finished Goods +

Wages Payable

- + WIP

- + CGS

+ - -

Raw Materials- +

THE BIG PICTURE

After Figure 5 is completed, we show how the information in the WIP T-account, the FG T-account, and the RM T-account relates to the Schedule of Cost of Goods Manufactured (CGM), theCost of Goods Sold (CGS) Schedule, and the Income Statement, as follows:

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Income Statement Sales Revenue $750 - CGS (unadjusted) (400) (see calculation below) Gross Margin $350 CGS Beginning FG inventory $0 + CGM + 1,500 (see calculation below)

- Ending FG inventory (1,100) (the bookshelves) CGS $400 (the table)

CGM DM used $2,900 + DL worked + 750 + Manufacturing overhead applied + 1,250 + Beginning WIP + 0

- Ending WIP (3,400) (the china cabinet) CGM $1,500 ($400 for the table + $1,100 for the bookshelves)

PART II

Part II of the simulation demonstrates the allocation of manufacturing overhead to theproducts. To complete the job cost sheets in Part I, the instructor just tells the students how muchmanufacturing overhead to charge to each job. In Part II, we discuss how the amounts are derived.We feel that this is an extremely important aspect of the simulation not only in understandingtraditional cost accounting, but in a subsequent understanding of activity-based costing, since thedifference between the two methods relates to the assignment of overhead costs.

Teaching opportunity: Explain the definition of manufacturing overhead and havethe class identify items in the simulation that constitute manufacturing overhead.

Examples:

‚ indirect materials (stain, glue, felt, sandpaper);* ‚ indirect labor (Production Supervisor’s salary, RM Warehouse Storekeeper’s salary,

Cost Accountant’s salary);*‚ depreciation or rent for factory (i.e., classroom);*‚ depreciation or rent for equipment (i.e., scissors, knife);*‚ utilities on factory;*‚ maintenance on factory;

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‚ property taxes on factory;‚ insurance on factory;‚ *items encountered during the classroom simulation in Part I.

Teaching opportunity: Note that indirect labor does not include the FG WarehouseSupervisor’s salary because it is a period (selling) cost rather than a product cost.

Teaching opportunity: Discuss the difficulty of charging manufacturing overheadto the jobs.

Explain that it may be impossible because of no direct cause/effect relationship, orit may not be economically practical to trace to the specific job. Also, discuss howan activity base should be selected and the problems involved with using one plant-wide cost driver.

The exercise now continues by first demonstrating the use of an actual costing system wherethe actual overhead will be allocated using DL hours as the cost driver. Assume that total overheadfor the period amounted to $1,500. Also, assume that only Jobs #1, #2, and #3 were worked onduring the period, resulting in a total of 50 DL hours (5 hours for Job #1, 10 hours for Job #2, and35 hours for Job #3). The plant-wide overhead rate is then computed as follows:

Actual Manufacturing Overhead Rate = $1,500 / 50 DL hours = $30 per DL hour

Teaching Opportunity: Discuss how actual manufacturing overhead is accumulatedthroughout the period and is added to the debit side of the Manufacturing Overheadaccount.

Now, the instructor fills out another set of Job Cost Sheets (see Figure 4). Overhead is allocated bymultiplying the $30 rate by the actual number of hours incurred by each job, as follows:

Job #1 Job#2 Job #3 Total

DM $200 DM $700 DM $2,000 DM $2,900

DL 75 (5 hrs. @ $15) DL 150 (10 hrs. @ $15) DL 525 (35 hrs. @ $15) DL 750 (50 hrs. @ $15)

O/H 150 (5 hrs. @ $30) O/H 300 (10 hrs. @ $30) O/H 1,050 (35 hrs. @ $30) O/H 1,500 (50 hrs. @ $30)

Total $425 Total $1,150 Total $3,575 Total $5,150

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Teaching Opportunity: Discussion of the problems associated with using an actualmanufacturing overhead rate and why a predetermined rate is used more often.

Next, the instructor shows how overhead would be applied in a normal costing system, usinga predetermined overhead rate. Suppose that at the beginning of the period, the company estimatedthat manufacturing overhead would amount to $1,000 and that a total of 40 DL hours would beworked on all three jobs. The predetermined overhead rate is then computed as follows:

Predetermined Manufacturing Overhead Rate = $1,000 / 40 DL hours = $25 per DL hour

At this time, the instructor fills out another set of Job Cost Sheets (see Figure 4) using thenormal costing system. Overhead is applied by multiplying the $25 predetermined overhead rateby the actual number of hours incurred by each job, as follows:

Job #1 Job#2 Job #3 Total

DM $200 DM $700 DM $2,000 DM $2,900

DL 75 (5 hrs. @ $15) DL 150 (10 hrs. @ $15) DL 525 (35 hrs. @ $15) DL 750 (50 hrs. @ $15)

O/H 125 (5 hrs. @ $25) O/H 250 (10 hrs. @ $25) O/H 875 (35 hrs. @ $25) O/H 1,250 (50 hrs. @ $25)

Total $400 Total $1,100 Total $3,400 Total $4,900

Note: These overhead amounts were the ones used in Part I of this exercise. The instructormay wish to compare these costs to the ones assigned earlier by the actual costing system.

Since the applied overhead of $1,250 is less than the actual overhead of $1,500, we have$250 of underapplied overhead.

Teaching Opportunity: Discussion of overapplied and underapplied overhead andhow these amounts are disposed of at the end of the period.

Using the most common approach for disposal of underapplied overhead, we close out themanufacturing overhead account in Figure 5 and add $250 to cost of goods sold.

Teaching Opportunity: Discussion of the possible benefits of using departmentaloverhead rates rather than one plant-wide overhead rate.

Let us assume that the Cutting Department is highly automated (capital intensive) and theFinishing Department requires a lot of manual labor (labor intensive). We can therefore get a moreaccurate measure of product cost by using machine hours as the allocation base in the Cutting

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Department (since machine hours “drive” more of the overhead in the Cutting Department) and byusing direct labor hours as the activity base in the Finishing Department (since direct labor hoursdrive most of the overhead in the Finishing Department).

INSTRUCTORS’ EXPERIENCES

This simulation has proven to be highly successful. It is not only an effective teachingmethod in terms of student comprehension and retention, but it is fun and provides a break from theregular classroom activities. Since job order costing is normally covered fairly early in the course,using this simulation gets the students interested in the course material from nearly the verybeginning.

The exercise takes approximately 75 minutes. Of course, the amount of time can varyaccording to how much discussion the instructor solicits on the various teaching opportunities thatare cited in the paper. The simulation can supplement or take the place of a traditional lecture. PartI and Part II can be separated into different consecutive days.

Students who have experienced this exercise have found it to be educational and fun. Manystudents have asked for another simulation after being exposed to this one. At the end of thesemester, students’ course evaluations commented on how much they remember from the simulationand how it helped them to understand job order costing. Occasionally, we receive e-mails about theexercise. One example is from a student who was taking cost accounting after having hadmanagerial accounting: “I just wanted to let you know that the way you explained inventory withthat skit still sticks in my mind, and I never really understood the flow of DM, WIP, and FG untilI was able to visualize it that day. It is definitely helping me a lot in my accounting class thissemester!” Another example is the following email received from an MBA student: “I also wantedto tell you that I really enjoyed last nights (sic) class. You mentioned that you had never done it inthat manner. I felt it was an excellent way to help us learn. I have never had a teacher who got thewhole class involved and paying attention to Accounting. :) It has always been a rough and hardsubject for me but by you presenting the material in such a way, I felt it helped me learn. So goodjob!”

To more formally assess students’ opinions about this job costing simulation, weadministered a survey to two sections of undergraduate students in introductory managerialaccounting courses after exposure to the simulation. We asked the students to respond to ninequestions regarding their views about the simulation and we used a five point scale where “StronglyAgree” = 5 and “Strongly Disagree” = 1. The results appear in Table 1.

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Table 1: Data from Student Survey

Mean(n = 61)

1. This simulation helped me to understand the flow of goods in a manufacturingorganization and the corresponding flow of product costs in the accounting system.

4.33

2. This simulation helped me to understand how direct materials and direct labor costs areaccumulated in a job-order cost system.

4.33

3. This simulation helped me to understand how overhead is allocated in a job-order costsystem.

4.20

4. This simulation helped me to understand how product cost is calculated in a job-ordercost system.

4.21

5. This simulation helped me to understand the difference between direct materials andindirect materials.

4.36

6. This simulation helped me to understand the difference between direct labor and indirectlabor.

4.33

7. This simulation helped me to understand the difference between actual manufacturingoverhead and applied manufacturing overhead.

4.10

8. The content of this simulation was meaningful and relevant. 4.25

9. Overall, I found this to be a valuable learning experience. 4.23

Response Scale Strongly Agree = 5Agree = 4Neutral = 3Disagree = 2Strongly Disagree = 1

The mean values from the 61 students are all greater than 4.00 for all nine questions. Thefirst seven questions deal with students’ understanding of specific aspects of job costing, such asoverhead allocation and the distinction between direct and indirect labor. The results indicate thatstudents believe the simulation helps them to understand various concepts relating to job costing.The last two questions are very general ones dealing with their overall views about the simulation.The results show that students feel the simulation to be a meaningful, relevant, and a valuablelearning experience.

REFERENCES

Burns, C.S. & S.K. Mills (1997). Bringing the factory to the classroom. Journal of Accountancy, (January), 56-60.

Davis, B.G. (1993). Tools for teaching. San Francisco, CA: Jossey-Bass Publishers.

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Dekkers, J. & S. Donatti (1981). The integration of research studies on the use of simulation as an instructional strategy.Journal of Educational Research, 74, 424-427.

Hilton, R. (2005). Managerial accounting. New York: McGraw-Hill Irwin.

McKeachie, W.J. (1994). Teaching tips: Strategies, research, and theory for college and university teachers, Lexington,MA: D.C. Heath and Company.

McKeachie, W.J. (1999). Teaching tips: Strategies, research, and theory for college and university teachers, Boston:Houghton Mifflin Company.

Morgan, S., L. Martin, B. Howard & P.H. Mihalek (2005). Active learning: What is it and why should I use it?,Developments in Business Simulations and Experiential Learning, 32, 219-223.

Roth, H.P. (2005). An active learning exercise illustrating a manufacturing process in a cost management class. DecisionSciences Journal of Innovative Education, (Fall), 367-374.

Schneider (2009) Managerial accounting: Manufacturing and service applications. Mason, OH: Cengage Learning.

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FACTORS INFLUENCING THE UNIVERSITYSELECTION OF INTERNATIONAL STUDENTS

Cynthia M. Daily, University of Arkansas at Little RockStephanie Farewell, University of Arkansas at Little Rock

Gaurav Kumar, University of Arkansas at Little Rock

ABSTRACT

The number of international students pursuing secondary education at United States (U.S.)universities has been increasing over the past 25 years, and is expected to continue into theforeseeable future. However, these students have a plethora of choices among universities in theU.S. and foreign countries. Universities must distinguish themselves if they hope to obtain the mostdesirable students from around the world. Previous research by Agarwal and Winkler (1985), Leeand Tan (1984), Mazzarol and Soutar (2002), and McMahon (1992) has identified a number offactors that influence the choice of educational programs. This paper builds on existing researchby re-examining some of those factors combined with additional factors and by examining the roleof accreditation by The Association to Advance Collegiate Schools of Business (AACSB).Specifically, we examine whether students know the meaning of AACSB accreditation, as definedby the AACSB, and the relative importance of AACSB accreditation on the university choice ofinternational students pursuing business degrees in a cross-section of public universities in thesoutheastern region of the U.S. Our study found that opportunities for post-graduate employment,availability of financial aid, institutional reputation, accessibility of information on the institutionand AACSB accreditation of the institution were the most important factors for internationalstudents in the choice of educational institution. However, further investigation shows thatinternational students may not fully understand the meaning of accreditation by The AACSB.

Keywords: Accreditation, Business Education, International Students

INTRODUCTION

The number of international students pursuing secondary education at United States (U.S.)universities has been increasing over the past 25 years, and is expected to continue into theforeseeable future. However, these students have a plethora of choices among universities in theU.S. and foreign countries. Universities must distinguish themselves if they hope to obtain the mostdesirable students from around the world. An investigation of the factors that are most important

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in university choice is an important step in allocating resources to attract the most desirableinternational students. Our study found that opportunities for post-graduate employment,availability of financial aid, reputation of the institution, accessibility of information on theinstitution and AACSB accreditation of the institution were the most important factors forinternational students. However, further investigation shows that international students may notfully understand the meaning of accreditation by AACSB.

There were 565,039 international students enrolled in U.S. higher education institutions in2004-2005 (eduPASS). These students represent more than two hundred countries and were equallydivided between those pursuing undergraduate degrees and those seeking graduate/professionaldegrees (edupass.org). Florida (2005, 99) provides an overview of the impact of foreign scholars onthe economy of the U.S.

i. Foreign-born scientists and engineers made up nearly a quarter of the science andengineering workforce (22 percent) in 2000, up from 14 percent in 1990. Foreign-born engineers make up about 40 percent of all U. S. engineering professors.

ii. Between 1990 and 2000, the percentage of international students among allbachelor’s-degree holders in the U.S. increased from 11 to 17 percent; the percentagewith a master’s degree from 19 to 29 percent; and PhDs from 24 to 38 percent.

iii. By the early 2000s, nearly a third of all graduate students in science and engineeringwere from outside the United States, including more than half of all PhDs inengineering, computer science, life sciences, and the physical sciences.

The continued growth of international scholars as consumers of U.S. higher educationprograms highlights the need to better understand this phenomenon. Previous research has examinedfactors that “push” a student to pursue educational opportunities abroad and “pull” the student to aparticular host county (e.g., Mazzarol and Soutar, 2002; Lee and Tan, 1984; Agarwal and Winkler,1985; McMahon, 1992). Although Mazzarol and Soutar (2002) investigate factors influencinginstitutional choice, the research stream has not been extended to business schools in particular. Weinvestigate the relevance of previously identified factors to foreign scholars in their choice of abusiness school, given that an international student has decided to pursue a business degree in theU.S. In addition, we investigate whether international students understand the meaning of TheAssociation to Advance Collegiate Schools of Business (AASCB) accreditation and whetheraccreditation is a factor that international students report as important in the choice of a businessschool.

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LITERATURE REVIEW

A significant stream of research has been amassed in an attempt to better understand thefactors that influence the decision of individuals to pursue secondary education overseas rather thanin their home country. While early studies commented on the post-World War II increase ininternational students, Cummings (1984) was one of the first to examine patterns of migration andimmigration for secondary education. Subsequent research has increased the breadth of factorsconsidered and the change across time.

McMahon (1992) examined the expansive phase of international education that occurredduring the 1960s and 1970s. The study hypothesized and found that the decision to study abroad bystudents from 18 developing nations could be explained by both “push” and “pull” factors; however,there were differences for the lower and higher income subsets, as well as, longitudinally. The“push” model examines the dynamics of the home country, encompassing factors that cause theindividual to seek an education abroad. “Push” model factors which were negatively correlatedinclude the home country’s relative economic strength and the lack of available educationalopportunities in the home country. The degree of involvement in international trade and thegovernment’s educational emphasis were positively correlated “push” factors. The “pull” modelexamines the dynamics of the host country and the factors that make it relatively more attractive tointernational students seeking a non-domestic education. Results of tests of the “pull” model findthat students’ attraction to a host country was positively correlated with the relative size of thestudents’ home country economy compared to the host country and the host nation political interestsin the home country; whereas, host nation support via scholarships or other financial assistance wasnegatively correlated (McMahon, 1992).

Mazzarol and Soutar (2002) suggest that the decision process of a student wanting to pursuehigher education in a foreign country consists of at least three distinct stages. In stage one, thedecision to study internationally, rather than domestically is made. This initial decision is influencedby the “push” factors previously identified by McMahon (1992). The second stage involves theselection of a host country. The selection of a host country is influenced by: (1) host countryknowledge and awareness, (2) recommendations of family and friends, (3) costs (monetary andsocial), (4) physical and economic environment, (5) geographic proximity to the home country, and(6) the presence of family and friends currently or formerly residing in the host country (Mazzarolet al., 1997, cited in Mazzarol and Soutar, 2002). Finally, in the third stage, the student decides theuniversity at which to pursue a higher education. Again, a variety of “pull” factors determine thisdecision.

Mazzarol and Soutar (2002) reports the results of four separate studies undertaken andpublished by Australian Education International, Department of Education Training and YouthAffairs in which students from four countries (Indonesia, Taiwan, India, and China) were surveyedto examine factors which influence the selection of a host country. The results of these studies show

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that at least fourteen factors, grouped into six categories, influence the decision to pursue aninternational education and these factors appear to be important, regardless of the student’s homecountry. Two factors were significant in the decision to study abroad. First, students had theperception that an education abroad was superior to a domestic education. Second, they felt a greaterawareness of “Western culture” could be achieved through international study. Factors whichsignificantly influenced the student’s choice of host country included: (1) the accessibility ofinformation on the host country, (2) the student’s existing perception of the host country, (3)perception of educational quality, and (4) whether the degree would be recognized when the studentreturned home. Further, recommendations from family and friends were important to the selectiondecision. Costs, monetary and social, were also a consideration in the selection decision;specifically, the availability of part-time work, a low crime-rate and the presence of an existinginternational student population representing the student’s home country impacted the selection.Environment was ranked as important to the decision with environment encompassing not only theclimate, but also perceptions of whether the host country was an exciting place to live and whetherthe host country would provide a studious environment. Finally, the presence of friends and relativescurrently studying in the host country was important to the selection decision.

Mazzarol and Soutar (2002) also investigate the factors which influence the selection of anAustralian educational institution for international and domestic students. This sample includedprimarily business majors (84 percent), which is reflective of the entire population of universitystudents in which 71 percent were business majors at the time (Mazzarol and Soutar, 2002). Incomparing domestic and international students it was found that the international students rankedsix variables as more important in their selection of a host institution than local students. Those sixvariables “were the quality and reputation of the institution, the recognition of the institution’squalifications in their own country, the international strategic alliances the institutions had, thequality of the institution’s staff, its alumni base and its existing international student population”(Mazzarol and Soutar, 2002:87).

CURRENT STUDY

We are not aware of any previous research that has examined the factors that foreign studentsconsider when choosing a business school in the U.S. Therefore, we investigate the relativeimportance of “push” and “pull” factors previously identified as important and extend theassessment to include the relevance of AACSB accreditation in the student’s choice of a businessschool. Although evidence suggests that accreditation is a significant factor in the selection of agraduate business institution for domestic students (Webb, 1993), its impact on the decision ofinternational students has not been examined.

Moreover, research has shown that, recruiters perceive institutional accreditation to be anindication of the program’s quality (Hardin and Stocks, 1995). Kim et al. (1996) found that salaries

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were higher for students graduating from accredited programs. Given that the previous studies havefound that it is important for the degree qualifications to be recognized in the student’s home countryit seems likely that students will perceive accreditation to be important. This is because accreditationis an internationally recognizable proxy for program quality.

The U.S. Department of Education does not accredit universities, but rather grantspermission to accrediting agencies. These accrediting agencies may specialize in regionalaccreditation (e.g., Southern Association of Colleges and Schools), program type (e.g., AmericanAssociation of the Collegiate Schools of Business), or educational type (e.g., Accrediting Councilfor Continuing Education and Training or Distance Education and Training Council). While thereare other accrediting agencies such as The Association of Collegiate Business Schools and Programs(ACBSP), we choose to focus specifically on AACSB accreditation because we believe it has thehighest "brand name" recognition to begin a research stream on the relative importance ofaccreditation to international students. Additionally, previous research (Hardin and Stocks, 1995)has shown that AACSB accreditation is considered important by the employers and Webb (1993)provides evidence that accreditation is a significant factor in the selection of a graduate businessinstitution for domestic students. Most of the other listed agencies indicate that their accreditationassesses whether the institution complies with minimum quality standards. For example, “The DETCAccrediting Commission identifies and accredits distance education and training institutions thathave attained and maintained the standards deemed necessary to operate a minimum level ofquality” (Distance Education and Training Council website). However, “AACSB Internationalaccreditation represents the highest standard of achievement for business schools, worldwide”(AACSB website). Given the disparate meanings conveyed by accreditation (minimum standardsversus highest standards) and its potential to impact the institutional selection process, we testwhether participants know the meaning of AACSB accreditation, as defined by The AACSB.

METHOD

Participants

We desired a sample size of 42 or more survey respondents. The target sample size relatesto an alpha level of 0.05 for analysis of variance and power of about 0.70 to detect a large effect(Myers and Well, 2003, p157). To achieve the desired sample size, students from eight universitybusiness schools in the United States were surveyed during the 2006-2007 academic year. Thebusiness schools selected represent a ‘convenience sample’ of the population of business schoolsin the U.S., as they were selected based upon the authors’ current and former affiliations.International student program offices provided email addresses for international students who haddeclared business majors. Students were contacted via email requesting their participation in thisstudy. This email assured the individuals of their anonymity, reminded them that participation was

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strictly voluntary, and provided a link to the survey which was hosted on the Survey Monkeywebsite. The initial email resulted in 22 responses. A reminder email was sent ten days after theinitial email, which resulted in 28 responses. Hence, 50 respondents provided complete surveys.

Instrument

As mentioned previously, the objective of the present study is to investigate the factors thatinfluence the decision of a foreign student to select a business institution in the U.S. In addition, weexamine whether AACSB accreditation contributes to this decision by the students. The surveyinstrument (see Appendix A) included three sections. The first section included two questions, oneaddressing the decision factors and another question allowing respondents to give additionalinformation about one of the decision factors. Section II assessed the respondent’s understandingof accreditation, while the final section gathered demographic data. Participants were also providedwith an open response question to indicate other factors that they deemed relevant to their decisionprocess, which were not included on the survey instrument.

The first question in Section I asked the respondents to rate the importance of the 17 decisionfactors when selecting a business degree program. The instrument used a 6 point Likert scale, with1 being little or no importance and 6 being extremely important. This is in contrast to the Mazzaroland Soutar (2002) study which used a 7 point Likert scale. Previous research (Lee et al., 2002)demonstrated that a cultural response bias exists when using Likert scales. In particular, Lee et al.(2002) found that participants from China and Japan were more likely to be indifferent to questions,as evidenced by the use of the scale mid-point than participants from the U.S. To minimize the riskof cultural disposition to the mid-point of the scale, a six point scale was used.

The instrument included factors that Mazzarol and Soutar (2002) identified as important foreither the selection of a host country or host institution. The first factor in the instrument (thenumber of international students) was found to significantly influence the foreign scholar’s decisionto choose a particular institution in Mazzarol and Soutar (2002). Mazzarol and Soutar (2002)examined the accessibility of information about the host country using four separate factors, eachof which was significant. Because our participant population has already decided to study in the U.S.we assess the single factor (accessibility of information on the institution). In addition, four factorsthat they found to be not important were included (tuition cost, accessibility of information, cost ofliving, and recommendations by non-family members (agents)). Four additional factors were added(availability of financial aid, athletic scholarships, AACSB accreditation, and the opportunity forpost-graduation employment) to assess their impact in the decision process based on the authors’beliefs from their interactions with foreign scholars. Factor 15 (urban/rural setting) was included toincorporate the trade-off between ‘an exciting place to live’ and ‘quiet studious environment’ thatwere previously identified as important in the host country selection decision. Therefore, thisinstrument builds on previous research and provides a model that can be used in future studies.

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After the participants assessed the relative importance of each decision factor they were allowed toprogress to the next section.

In the second section, a multiple choice question was used to test the respondent’sunderstanding of AACSB accreditation. The website of AACSB International states that “AACSBaccreditation represents the highest standard of achievement for business schools, worldwide,” andthat institutions that earn this accreditation confirm their commitment to quality and continuousimprovement through a rigorous and comprehensive peer review. The survey asked “Based on yourunderstanding of AACSB accreditation, which of the following statements is true: (1) AACSB isthe highest standard of excellence in Business Education (correct response); (2) AACSB representsthe minimum standards required for Business education programs; (3) I do not know about AACSBaccreditation.”

RESULTS

Since the sample used in this study represents a convenience sample, the results cannot beprojected onto the population as a whole. However, the results can be a first step in increasing ourunderstanding of factors that might influence university choice among international students.Respondents to our survey represent 27 countries. Table 1 presents the countries represented in thissample and the number of responses (if greater than 1) from each country. The students respondingprovided a varied sample of nationalities.

Table 1: Number of Respondents by Country

Argentina (2) India (13) Slovakia

Azerbaijan Jamaica Taiwan

Bangladesh Japan (4) Thailand

Brazil Lebanon Togo (West Africa)

Bulgaria Mexico Turkey (4)

Chile Moldova Uzbekistan

China (2) Nepal Vietnam

Croatia Pakistan No Response (1)

Czech Republic (3) Saudi Arabia

Fiji Islands Serbia, Europe

Number of respondents in parentheses if greater than one.

The highest number of responses came from students that identified India as their homecountry. This is consistent with overall population of international students in the U.S., wherein,

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students from India represent the largest proportion of the total international student population(eduPASS).

Demographic information reveals that respondents are evenly divided between the genders,with 25 males and 25 females. Most of the respondents were single (32 or 64%), 16 were married(32%) and two were divorced. All of the respondents were business majors with accounting majorsrepresenting the largest group (20.8% majoring in accounting). The breakdown of majors and thenumber in each major are presented in Table 2.

Table 2: Number of Respondents by Major

Accounting (11) Information Systems (6)

Management (8) Economics (5)

Marketing (7) International Business (4)

Finance (6) Other Business Majors (3)

Number of respondents in parentheses

Figure 1 provides a graphical representation of the responses to each factor split by whetherthe response indicated some degree of importance (points 4 through 6 on the Likert scale) orunimportant (points 1 through 3 on the Likert scale). Table 3 provides the descriptive statistics forthe importance of each factor to the student’s selection of a business school. Using t-tests to examinethe difference between the mean response to each decision factor indicates that these factors can bedivided into three groups. The most important decision factors are the opportunities for post-graduation employment, financial aid and reputation of the institution. These three factors are notsignificantly different from each other but significantly more important (" = .04) than the secondgroup of factors - all having a degree of importance to the students. The second group of decisionfactors includes accessibility of information on the institution, AACSB accreditation, tuition, costof living in the area and public safety in the area. These five factors are not significantly differentfrom each other, but significantly more important (" = .02) than the third group of factors – all ofwhich are relatively unimportant to the respondents. The number of international students at theinstitution and availability of athletic scholarships were the least important decision factors.

Figure 1: Percentage of Sample Responding to Each Question

Factors with a response between 1 to 3 on a Likert scale are classified as Unimportant and factors witha response between 4 to 6 are classified as Important

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Table 3: Mean Responses by Factor

Q# Factor Mean StandardDeviation

Paired SamplesT-test (2-tailed)

11 Opportunities -post-graduation employment 4.98 1.500.73

8 Financial Aid 4.90 1.540.72

3 Reputation of the institution 4.82 1.100.04

2 Accessibility of information on the institution 4.50 1.430.78

4 AACSB Accreditation 4.42 1.720.65

7 Tuition 4.26 1.901.00

10 Cost of living in the area 4.26 1.440.35

12 Public Safety in the area 4.10 1.520.02

17 Recommendation by non-family members 3.46 1.430.57

6 Friends/relatives already living in the area 3.28 1.710.94

15 Urban/rural setting 3.26 1.560.94

5 Friends/relatives attending the university 3.24 1.760.88

13 Climate 3.20 1.630.83

14 Public/private institution 3.14 1.64 1.00

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Table 3: Mean Responses by Factor

Q# Factor Mean StandardDeviation

Paired SamplesT-test (2-tailed)


16 Recommendation by parents/relatives 3.14 1.580.21

9 Availability of athletic scholarships 2.70 2.040.87

1 The number of international students 2.64 1.48

(1= Little or no importance to decision; 6=Extremly important)

Several analysis of variance (ANOVA) studies revealed some interesting information aboutthe subjects. The ANOVA model used for all studies utilizes Tukey’s HSD (a conservative test) forpairwise comparisons, which is appropriate for unequal group sizes. An ANOVA with decisionfactors 1-17 as the dependent variables and gender as the independent variable showed significantdifferences ("=0.044) between males and females only on their response to the importance of tuitionamount. Females place more importance on the amount of tuition (:=4.80; sd=1.61) than did themale respondents (:=3.72; sd=2.05).

An ANOVA with decision factors 1-17 as the dependent variables and marital status as theindependent variable showed significant differences between groups (married, divorced or single)and their responses to three of the questions (see Table 4)

Table 4: The Impact of Marital Status on Responses

Question: How important were these factors in your choice ofuniversity/college?

Group Comparisons(mean and standard deviation)

Tukey’sHSD

2. Accessibility of information on the institution Married (:=5.13; sd=0.96) & Single (:=4.19; sd=1.53) 0.082

4. AACSB Accreditation

Married (:=4.81; sd=1.64) & Divorced (:=1.50; sd=0.71) 0.025

Divorced (:=1.50; sd=0.71)& Single (:=4.41; sd=1.64) 0.047

16. Recommendation by parents/relatives Married (:=3.81; sd=1.47) & Single (:=2.81; sd=1.57) 0.096

Accessibility of information was marginally more important to the married subjects than it

was to the single subjects. AACSB accreditation was equally important to the married and singlesubjects, but not as important for those two individuals that were divorced. Recommendations byparents/relatives were considered more important by the married respondents than they were by thesingle respondents.

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The mean response to whether or not AACSB accreditation was important was 4.42 makingit more than marginally important. Table 5 reports the results of an analysis of variance between theimportance of AACSB accreditation and the subject’s understanding of AACSB accreditation.Tukey’s HSD for post-hoc pairwise comparisons reveals that respondents that did not know whataccreditation meant found it significantly less important than those that thought that it was thehighest standard and those that thought that it was the minimum standard. There was no significantdifference in the importance of AACSB accreditation between those that thought this accreditationto be highest standard (which it is) and those that thought this accreditation to be the lowest standard(which it is not).

Table 5: Importance of AACSB Accreditation by Groups

Comparisons (means and standard deviations) Tukey’s HSD

Highest Standard (:=4.94; sd=1.73) and unknown (:=3.12; sd=1.38) 0.002

Minimum Standard (:=5.31; sd=1.20) and unknown (:=3.12; sd=1.38) 0.000

Highest Standard (:=4.94; sd=1.73) and Minimum Standard (:=5.31; sd=1.20) 0.726

The mean response to whether or not post-graduation employment opportunities areimportant was 4.98 making this the most important factor of this study. As can be seen in Table 6,an analysis of variance between the importance of post-graduation employment opportunities andwhether or not the individual intends to return to his (her) home country revealed that all groups(those that plan to return, those that do not plan to return and those that are undecided) found post-graduation employment to be equally important.

Table 6: Post-graduation Employment Opportunities

Comparison of the importance of post-graduation employment opportunities according towhether or not the individual plans to return to their home country.

Tukey’sHSD

Yes (:=4.69; sd=1.75) and No (:=5.00; sd=1.63) 0.865

Yes (:=4.69; sd=1.75) and Undecided (:=5.13; sd=1.33) 0.690

No (:=5.00; sd=1.63) and Undecided (:=5.13; sd=1.33) 0.969

DISCUSSION

This study investigated the relative importance of 17 decision factors, including AACSBaccreditation, to international students pursuing a business degree in the U.S. The factors that arefound to be the most important include opportunities for post-graduation employment, availability

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of financial aid, and reputation of the institution. These three factors are statistically more importantthan the second set of factors, which include accessibility of information, AACSB accreditation,tuition, cost of living in the area and public safety. However, the factors in the second group eachhave mean responses ranging from 4.10 to 4.50 meaning that respondents find these factors to beimportant to their decision regarding university of attendance. The remaining factors have meanresponses ranging from 2.64 to 3.46 and although they are important to some respondents, they arefound to be less important than the previously mentioned factors.

We find mixed results in comparing the results of this study to research using universitystudents studying abroad in countries other than the U.S. The results of this study confirmed someof the findings observed by Mazzarol and Soutar (2002). The mean response for, ‘accessibility ofinformation on the institution’ and ‘reputation of the institution were consistent with previousresearch. The mean responses for factors 5 and 6, ‘friends/relatives attending the university’ and‘living in the area’, respectively, were consistent with previous research in that they were lessimportant than other factors in the selection of a host country. Further, the response on ‘public safetyin the area’ was consistent with prior research.

On the other hand, some results contradicted those observed by Mazzarol and Soutar (2002).While ‘the number of international students’ was previously shown to be significant, we find thatthis is not the case for our participants. The results of this study find that ‘tuition’ and ‘financial aid’were significantly important to the selection process while prior research found that those factorswere only of moderate importance. The ‘cost of living in the area’ factor is slightly more importantthan the results of previous studies. The ‘climate’ in the area was found to be less important than theresults of previous research. The responses on ‘Recommendation by parents/relatives’ and‘recommendation by non-family members’ were not consistent with prior research, wherein we findthat these factors were less important for our participants than participants in the Mazzarol andSoutar (2002) studies.

We find that while international students do not necessarily understand the meaning ofAACSB accreditation, they do understand that accreditation is an important consideration in theselection of a business school. This may mean that AACSB International needs to better market themeaning of accreditation to potential students, to recruiting agencies, and international studentinformation websites. For example, a web query provided a link to eduPASS.org. At this site(eduPass(b)) visitors are given the information that “The U.S. government does not monitor thequality of U.S. colleges and universities, as does the ministry of education in other countries.Instead, the U.S. Department of Education approves accrediting agencies. These accreditingagencies review a school’s educational program for quality, and certify that the school meets aminimal set of standards.” While this definition of accreditation as a minimum standard may be truefor some accrediting agencies it is not in line with the definition provided by AACSB. Therefore,given that many international students may begin their search for a host country and host institutionusing an internet search it is easy to see how they may misinterpret the meaning of accreditation. In

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addition, the colleges which are accredited by AACSB should emphasize the importance of thisaccreditation so that the prospective students consider this factor in their decision.

This study contributes to the existing body of literature on the decision factors of importanceto international students in the selection of a host institution. We have extended the body ofknowledge to specifically examine business school students. The information gathered on the impactof AACSB accreditation should be relevant to both institutions and the AACSB as an impetus toimprove their marketing efforts.

Accessibility of information on the institution (mean of 4.50) was important to participantsand this issue is one that can be easily addressed by universities. Besides making sure that they arelisted on sites such as eduPASS.org, universities can provide links from their home page forprospective international students. Information can be provided about their institution, as well asthe factors found in this study to be important to prospective international students.

LIMITATIONS AND FUTURE RESEARCH

As with all research, interpretation of this study’s results is subject to several limitations,including: the use of a non-random sample and conducting the assessment after rather than beforethe participants had decided on a business school. In addition, it is hard to isolate the effect ofAACSB accreditation given that schools that are accredited often have other factors which affectthe school’s ‘attractiveness’ to international students. While the results cannot be projected to theentire population of international students studying in the U.S., the information can provide insightsinto their business school selection criteria and provide the basis for further study.

The most important factor in our study was opportunities for post-graduation employment.Upon further examination we found no significant differences in importance when subjects aredivided according to whether they plan to return home after graduation. Further research should bemore specific and ask about opportunities in their home country and their host country. Given thatthis study and previous research on host country institution selection have surveyed students thatwere currently studying in the host country, there is possibly a self-selection bias impacting therelative importance of some factors. Future research could also examine this possible self-selectionbias by examining the factors that students attending AACSB accredited institutions around theglobe consider important in the selection of an educational institution. Further, future research couldinclude experiments that isolate the effect of ‘accreditation’ on educational institution choice. Inaddition, research could focus on factors that students report to be important apriori (both at theundergraduate and graduate level, as well as, for traditional and non-traditional age undergraduatestudents). The results could then be compared to the factors inherent to the educational institutionchosen. Finally, international students could be surveyed at the completion of their studies todetermine which factors they felt should have been important in the selection of a U.S. educationalinstitution.

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Association for the Advancement of Collegiate Schools of Business. www.aacsb.edu.

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Myers, J.L. and A.D. Well (2003), Research Design and Statistical Analysis, 2nd edition, Lawrence Erlbaum Associates,New Jersey.

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AUTHORS’ NOTES

Authors names appear in alphabetical order. All authors contributed equally.

The authors would like to thank participants at the Allied Academies’ 2008 Spring International Conference andparticipants at the American Accounting Association 2008 Annual Meeting Research Interaction Forum.

APPENDIX ASURVEY QUESTIONS

The following is a list of the survey questions:

(Section I)

1. Indicate how important each of the following factors were in your choice of university/college (on a scale of1 to 6, with 1 being of little or no importance and 6 being of extreme importance).

# The number of international students# Accessibility of information on the institution# Reputation of the institution# AACSB (Association to Advance Collegiate Schools of Business) accreditation# Friends/relatives attending the university# Friends/relatives already living in the area# Tuition# Financial aid# Availability of athletic scholarships# Cost of living in the area# Opportunity for post-graduation employment# Public safety in the area# Climate# Public/Private institution# Urban/rural setting# Recommendation by parents/relatives# Recommendation by non-family members

2. If you received recommendations from non-family members, please indicate the relationship (i.e. teacher,trusted friend, employer, etc.):

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(Section II)

3. Based on your understanding of AACSB accreditation, which of the following statements is true:

# AACSB is the highest standard of excellence in Business Education.# AACSB represents the minimum standards required for Business education programs.# I do not know about AACSB accreditation.

(Section III)

4. Gender

# male# female

5. Marital status

# married# single# divorced# other

6. Country of Origin

# Mexico# Canada# India# France# Italy# other ( please specifiy)

7. Do you plan to return to your home country after completing your education?

# yes# no# undecided

8. What is your primary major?

# Accounting# Economics# Finance# Management# Marketing# Information Systems# Other (please specify)

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9. What is your minor?

# Accounting# Economics# Finance# Management# Marketing# Information Systems# Other (please specify)

10. Please provide any comments about other factors that you think were important to your decision that are notincluded in the above list.

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CREATING ACTIVE LEARNING APPLICATIONS ANDOPPORTUNITIES FOR AN ON-LINE LEADERSHIP

COURSE

Charles A. Griffin, Northern Arizona UniversityChris A. Lockwood, Northern Arizona University

ABSTRACT

This paper describes the creation of an on-line leadership course that retained as much ofthe rich, interactive nature of the face-to-face version as possible. The seven “best practice” designcriteria offered by Chickering and Reisser (1993) are discussed as they relate to specific coursedesign and instructional requirements for instructor orientation, course management organizationand tool use, community building as well as the development of thematic modules and theirassociated assignments. Student comments provided by a case study of the on-line course (Griffin,2007) are provided that support the efficacy of this approach.

INTRODUCTION

The growing popularity and acceptance of web-delivered education make it an attractive anddesired option for expanding the educational opportunities available to students (Petrides, 2002;Rivera & Rice, 2002; Robinson & Stull, 2006). Not surprisingly, institutions of higher learning areactively expanding web-based distance education offerings as a means of capturing increased coursedemand and student population (Hunt, 2005, Rivera & Rice, 2002; Waits & Lewis, 2003). NorthernArizona University (NAU) is no different. The W. A. Franke College of Business (FCB) at NAUdeveloped on-line course offerings to support a state-wide Bachelor of Science in BusinessAdministration degree to meet the needs of Arizona’s place-bound students. This article describesthe development of one of these on-line courses, MGT 311 Leadership.

FCB has offered a successful face-to-face delivery of the leadership course based on adultand cooperative learning techniques for several years. The development of this course wasinnovative in its use of adult educational techniques that encourage students to actively constructleadership theory and gain practical leadership experience. The course also offered strong studentinteraction through extensive in-class small group discussion and critical analysis activities. Thus,the challenge was to develop an on-line version of the course that retained as much of the rich,interactive nature of the face-to-face experience as possible. After an extensive literature review

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seeking guidance to address the challenge, we decided to design the on-line course based on theseven “best practice” design criteria for distance learning (Chickering & Reisser, 1993: DIIA, 2005)paraphrased below:

1. Encourage contact between students and the faculty. 2. Develop reciprocity, interaction, collaboration and cooperation among the students.3. Encourage active and constructive-oriented learning. 4. Provide prompt feedback. 5. Emphasize time on task. 6. Communicate high expectations. 7. Respect students’ diverse talents and ways of learning.

Additionally, course design required following the same master syllabus used to create the“working” syllabus of the face-to-face version of MGT311. FCB requires master syllabi thatdelineate learning outcomes and expected content to encourage consistency across multiple sectionsof the same course offered by multiple faculty. It was also decided to adopt the same text used inthe face-to-face course, Leaders & The Leadership Process: Readings, Self-Assessments &Applications by J. Pierce and J. Newstrom (2006). The text was originally selected for its uniquecombination of conceptual and empirical readings, coverage of the major leadership researchstreams, self-assessment exercises, extensive vocabulary and the authors’ perception that it helpedstudents move beyond theory and empiricism to the practice of leadership. That said, the authorsbelieve the design considerations discussed below allow the use of alternative text choices. Theimportant consideration is establishing a tight linkage between the text chosen and the design of theon-line course.

COURSE DESIGN

The challenge, as noted above, was to create an on-line leadership course that provided alearning experience based on leadership theories that also incorporated an active learningenvironment rich in practical leadership application. To facilitate meeting this challenge weoriginally selected the WebCT course management system (an integrated set of web-coursedevelopment tools) due to its ability to support the creation of both asynchronous and synchronouslearning environments. The course management system was later transitioned to Blackboard Vista(Bb Vista) when the university adopted it as its new on-line course management system.

The seven best practices necessitated unique design and instructional requirements forinstructor orientation, course management organization and tool use, community building, as wellas the development of thematic modules and their associated assignments. Each of these areas isdiscussed below with the authors’ rationale for the design and delivery of the on-line course.

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Instructor Orientation

For at least the past ten years the expansion of distance education has necessitated facultydelivering distance education re-examine the way teaching and learning take place. What hasevolved, in this alternative to the traditional classroom, is a new paradigm of teaching and learning.The development of this new paradigm was required because many of the established assumptionsof teaching and learning practiced in the traditional lecture-based classroom do not hold forsuccessful teaching and learning in the distance education environment (Palloff & Pratt, 1999).

Several key differences between the traditional lecture-based classroom and distance learningexist. These include faculty roles, use of technology, lesson organization, and the need forcollaborative learning. In making the transition from the classroom to on-line instruction, facultymust concern themselves with multiple pedagogical, social, managerial and technical issues.

One issue is the role of the on-line faculty. The faculty’s role has evolved from lecturer ina traditional classroom to a facilitator of learning in the virtual classroom (Simonson, Smaldino,Albright, & Zvacek, 2003). Lesson organization and design must adapt to a student-centeredapproach that shifts the focus from the faculty to the student learner. And it must be noted this moveis currently in play in the face-to-face section of MGT 311 that inspired the design of the distancelearning section.

Organizational issues such as lesson structure, use of visuals, and time allotment becomeincreasingly important. The on-line faculty must be even more concerned with class structure andhow to encourage a class to build “community.” In addition, faculty must be concerned with studentaccess and use of computer technology essential to the class. Does the student possess the accessand knowledge required to be successful in the on-line classroom? It has been the authors’experience, especially in adult education, that this should not be taken for granted.

On-line faculty must be able to establish a collaborative learning environment. For an on-line class to be successful faculty must facilitate the creation of a playing field with equalparticipation between the facilitator and all students in the class. High levels of interaction amongall involved in the virtual classroom insure a rich and powerful experience (Palloff & Pratt, 1999).Thus, there is a need to build a sense of community among participants.

Bd Vista Course Management System

The first step in creating (the web-based) MGT 311 was meeting and training with theuniversity staff dedicated to helping instructors create and manage virtual classrooms. This process,which included both one-on-one advice and assistance sessions as well as a series of small classroomtraining sessions with fellow on-line instructors, encompassed approximately twelve hours over atwo month period. Topics that were initially addressed included taking the specific courserequirements and creating the virtual classroom using the latest in technology and learning

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techniques. Once the course website was created, faculty training focused on how to manage theon-line course tools such as grading, testing, on-line communications, and other topics required tocreate an on-line learning community. However, it must be noted, instructor training did not stoponce the course was offered. During the first pilot semester of MGT 311 the instructor continuedto use the support staff as a valuable resource for questions and advice as issues came up.

In the Bd Vista course management system the course content is contained within a singlecourse website and contains both synchronous and asynchronous tools to facilitate communication,therefore learning, in the on-line virtual classroom. The synchronous tool allows faculty to easilycreate and offer a chat room for the students to ‘meet’ virtually when time was a critical factor inmeeting group assignment deadlines. The asynchronous tools include e-mail and discussion boardswhich allow faculty and students to meet virtually and interact yet provides flexibility in time andspace. Thus, the on-line course was not designed to be a passive, electronic correspondence course.It was designed so that students became actively engaged in a transformative experience by learningnew technology, working in a web-based environment, communicating in groups and with faculty,and reflecting on leadership as it pertains to their personal experiences. The importance ofcommunity to a web-based course cannot be overstated. The Bd Vista toolset allows faculty tocreate and nurture an active, collaborative approach to learning. The course sought to create a senseof autonomy, initiative, and creativity while encouraging questioning, critical thinking, dialogue,and collaboration.

While we used Bd Vista, there are several course management suites available that providesimilar features for instructors preparing on-line versions of their courses. Bd Vista was chosensolely because it is the course management suite used by NAU.

Community Building

The goal in building the course was to simultaneously create a community where learningtakes place among students themselves, between students and faculty, and collaboration in learningthat will result from these interactions. MGT 311 was designed to foster active interaction involvingboth course content and communication, collaborative learning, socially constructed meanings,sharing of resources, and support between learners (Palloff & Pratt, 1999). It is this strong learningcommunity that is the signature feature of MGT 311.

Students taking on-line classes using computers miles apart at different times of the day oftenfeel isolated. This feeling of isolation can be overcome by creating an on-line community oflearners who support one another. Community building is an important issue in distance learningbecause it impacts student satisfaction, retention, and learning. Community building refers tocreating a sense of belonging, of continuity, of being connected to others and to ideas and values.A community of learners is a group of participants in a course with a shared purpose, goodcommunications, and a climate with justice, caring, and discipline (Brown, 2001).

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The expansion in distance education and recent innovations in technology have allowed forincreasing interaction between and among learners and faculty. Multiple studies have concludedthat increased levels of interaction result in increased motivation, positive attitudes toward learning,higher satisfaction with instruction, deeper, more meaningful learning, and higher achievement(Sutton, 1999).

Distance educators have identified four types of interaction: learner-content, learner-instructor, learner-learner, and learner-interface (Hillman, Willis, & Gunawardena, 1994; Moore,1989). The interaction that takes place between the learner and the content is probably the mostbasic of the four types of interaction. The change we call learning takes place when the learnerinteracts with the content. Another type of interaction, learner-faculty, is regarded as essential bymany educators, and as highly desirable by many learners (Moore, 1989). The faculty serves as anexpert who, in the case of on-line learning, facilitates the instruction to stimulate students’ interestsand motivate students (Sutton, 1999). Historically, learner-learner interaction has not been asignificant part of education. Interaction has been limited to learner-content and learner-faculty. With the development of distance-education technology, this type of interaction has becomeeasier to create and support. Learner-learner interaction can be an extremely valuable resource forlearning, and is sometimes even essential (Moore, 1989). The fourth type of interaction that isunique to distance education, learner-interface, was added to Moore’s (1989) three types ofinteraction by Hillman, Willis, and Gunawardena (1994). These authors describe the learner-interface interaction as the interaction that takes place between the learner and thetechnology. Students must use the technology to interact with the content, the faculty, and otherstudents. In many distance-education classrooms, without learner-interface interaction, the otherthree types of interaction cannot take place (Sutton, 1999).

MGT 311 was constructed to facilitate the development of an on-line community that fostersactive interaction involving both course content and communication, collaborative learning, sociallyconstructed meanings, sharing of resources, and support between learners (Palloff & Pratt, 1999).In doing so, the course simultaneously created a learning community in which learning takes placebetween students themselves, between students and the instructor, and in a collaboration of learningthat resulted from these interactions (Palloff & Pratt, 1999).

Thematic Modules

The on-line course, like its face-to-face parent, is an introduction to leadership that definesleadership and explores the basic theories and issues related to leadership in the Twenty -firstCentury. To accomplish this goal the on-line version was organized into six learning and theme-based modules over a sixteen-week academic semester. The course was structured by creatingthemes as building blocks to allow students to basically crawl, walk and then run as theyaccomplished the on-line delivery learning objectives. The rationale for the learning module

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building blocks can be found in the learning environment. A student in an on-line course must firstdemonstrate a mastery of the computer skills and course web tools required for them to be successfulin a virtual classroom. Once this can be instructor-verified by course assignments in the firstmodule, the student can then be allowed to remain in the virtual classroom to fully participate. Thesix module instructional themes include: introduction to leadership, leadership traits and behaviorsfor success, leader-follower and situational dynamics, diversity in leadership, divergent thoughts inleadership, and the capstone self-assessment.

In Module One the student logs in and explores the course organization and layout, withina standard Bb Vista course site design. The course home page allows linkage to the virtualclassroom with course content, syllabus, communications tools, grades, calendar, and resourcesupport easily available. The students learn their way around the course which, in addition tonavigational and course management tools, offers a module introduction, objectives, key conceptsand terms, assignments, and an end-of-module quiz. This same organization is also used insubsequent modules. The modules are designed to be accomplished in numerical order. Successfulmodule completion, as determined by faculty-set scores for end-of-module quizzes, allowed studentsaccess to subsequent modules.

During the first two weeks of the term Module One introduces leadership theory to thestudents and sets the stage for course organization and flow. Students are asked: What does the termleadership mean to you? How would you define leadership? How does it differ from management?What processes do we associate with leadership? They then explore and attempt to answer thesequestions in Module One.

Modules Two to Five are structured along similar lines with required readings, individualpapers, group interviews and module quizzes. Module Two focuses on the themes of leadershiptraits and behaviors for success. Module Three focuses on the leader, follower and situationaldynamics. Module Four delves into the relationship between diversity and leadership. Module Fiveexplores several themes concerning divergent thoughts on leadership.

The last module, Module Six, is the capstone module of the course. There are two capstoneassignments. One assignment is an individual assignment where the student writes a leadershipself-improvement plan based on a personal assessment of their strengths and weakness as a leader.The final group project is to create a group critical assessment paper offering a judgment as towhether or not the group evolved over the process of the semester into a ‘team’ as defined in the textand its relationship to leadership.

Module Assignments

The Module One objectives and key terms and concepts focus on verifying the student hasthe prerequisite on-line skills to take the course. The student demonstrates the ability to successfullyuse the following WebCT tools: e-mail, topic discussion, assignment drop box, chat, and quiz. The

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student e-mails the instructor within WebCT stating that she/he has read the course syllabus,understands and will comply with its requirements. The student posts an individual one-page paperon the definition of leadership and responds to at least two other student submissions. Next, thestudent posts a personal resume to the assignment drop box for review by the instructor. Lastly, thestudent contacts at least one fellow student and arranges a chat time to discuss perceived differencesbetween leadership and management. At the completion of the module, a quiz is taken to validatethat the student understands the module objectives and is ready to move to Module Two. Themodule quiz is ten questions taken from key words and concepts from the module reading(s). Themodule quizzes are graded and the student must score at least 80% to move to the next module.

The rationale for Module One individual assignments is clear and critical to a studentbeginning the course. In Module One, the student is welcomed as a member of the learningcommunity known as MGT 311. The student not only demonstrates the ability to successfully usethe WebCT tools, but also the faculty begins to facilitate and encourage contact between studentsand the faculty, initiates the development of reciprocity, interaction, collaboration and cooperationamong the students, provides prompt faculty feedback, emphasizes time on task, communicates highexpectations, and lastly, sets the stage for respecting student’s diverse talents and ways of learning.Finally, before moving into Module Two, the faculty, at the conclusion of Module One, establishesstudent working groups.

In Module Two each student individually reads the assigned chapters, writes and posts a two-page double-spaced critical analysis of the readings from each chapter. This paper is not a summarybut a critical analysis of the readings as they relate to the module objectives and key terms andconcepts. The student will then post the paper to the chapter topic on the discussion board andcomment on at least two other student papers from that topic. As noted above, the faculty, at theconclusion to Module One, establishes student working groups. Each group (consisting of four tofive students) will then develop a group treatise or code of conduct, posted by each group to thegroup discussion board, as the first group assignment of the course.

In addition to the individual writing assignments common to Modules Two to Five, groupinterview assignments begin with Module Three and are conducted though Module Six. Each groupmember interviews a leader within their community. The topic for this interview depends on themodule as it pertains to that leader’s profession. The profession could be business, civic, educationor military. On a rotational basis, one group member serves as the leader/recorder to consolidatethe individual interviews into a summary paper of the interviews as they relate to the leadershiptheme of that module. The leader/recorder also includes at least two Internet sources concerning theleadership theme of that module. The group report is no less than four and no more than six double-spaced pages in APA style (APA, 2001) and is posted to the group discussion board for the module.The individuals conducting the interviews gain approval from the faculty for proposed intervieweesand interview questions by corresponding in the topic discussion board. A link providing guidanceto conducting interviews is provided. Once approved, the interviews are conducted and consolidated

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by the leader/group recorder into a final product. Each member of the group must provide input andapprove the final group report before posting.

The rationale for Module Two to Five group assignments is critical to a student meeting akey pedagogical goal of the course. This goal is the active construction and practical applicationof leadership theory in an on-line environment. Beginning with Module Two the five memberstudent groups execute group projects and with each new module rotate the group leadership so eachgroup student member will lead a virtual semi-independent working group at least once during theterm.

The last module, Module Six, is the capstone module of the course. There are two capstoneassignments intended to be a critical analytical discussion encompassing all material and experiencesfrom the class. The first assignment is an individual assignment in which the student writes aleadership self-improvement plan. This includes an individual self-assessment of the student’s ownperceived strengths and weaknesses as a leader and their plan to improve as a leader. Thisassignment reinforces how important it is for a leader to fully understand their self-efficacy beforethey attempt to learn and understand those they may lead. The assignment also supports two keyobjectives of the course, being able to identify a student’s own perceived strengths and weaknessesas a leader and their plan to improve. The second Module Six assignment is a final group projectto create a group critical assessment paper offering a judgment as to whether or not the semi-independent virtual student group evolved over the process of the semester into a cohesive ‘team’as defined in the text. The first rationale for this final group project was to have each group memberconduct an assessment of their success or failure in evolving into an on-line community that fostersactive interaction and communication, collaborative learning, socially constructed meanings, sharingof resources, and support between learners (Palloff & Pratt, 1999). The second rationale for thissecond module six assignment was to have students identify the challenges of leading a semi-independent working group.

The overall student reaction to the modular organization of MGT 311 was favorable. Thestudents indicated the organization of the course supported their needs and expectations for aleadership course. These student reactions are highlighted in the next section.

STUDENT REACTION

Conducting a case study of MGT311, Griffin (2007) offered clear evidence students believedthe on-line course lived up to their expectations and met their needs for an on-line leadership course.When presented the statement, “This course met my needs for a leadership course,” 75% of thereporting students responded, “they strongly agree” and the other 25% responded, “they agree”.When presented the statement “I would rate my overall experience in this class as a positive one,”67% of the reporting students responded, “they strongly agree” and the other 33% responded, “theyagree” (Griffin, 2007).

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“As we wind down this module, and this course for that matter, I feel we are allbetter leaders and followers because of this class” (Griffin, 2007).

Based on their course experience 77% of the reporting students reported “strongly agree”and 23% “agree” when asked if they would take another on-line course at FCB, and an identical77% reported “strongly agree” and the remaining 23% “agree” when asked if they wouldrecommend MGT 311 to someone interested in leadership instruction. The following responsesrepresented the common themes “working together with my group helped me gain a betterunderstanding of leadership and gave me much needed experience on assuming a leadership role,”and, “great experiences throughout the course, I found myself thinking about and applying thetheories and ideas throughout my work day” (Griffin, 2007).

The student feedback related to their perceptions, experiences and success in the course wassupported by the literature. On-line courses and programs continue to increase in frequency inhigher education. Students are increasingly demanding on-line access, and universities and collegesare working to meet the demand. With the increasing prevalence of Internet-based courses, it isimportant to examine students’ experiences in order to provide an improved learning environment(Singleton, Hill &, Koh, 2004; Howland & Moore, 2002).

Students have identified several factors contributing to successful on-line courses. Theseincluded excellent course design, convenience, flexibility, learner motivation, time management,and comfort with on-line technologies (Singleton, Hill &, Koh, 2004; Howland & Moore, 2002).

The implications are clear. The on-line students of MGT 311 believed theoretical andpractical leadership instruction can be offered effectively in a totally web-based learningenvironment. And based on the vast majority of student feedback, the MGT 311 students will bothtake more on-line courses and recommend this course to students interested in leadership instruction.As one representative student of the on-line section of MGT 311 put it, “we learned through hands-on experiences, living the chapters of the text, in a well structured course.” MGT 311 willpotentially open the door for many place-bound and time-bound students of leadership. However,the course may not be for everyone as noted earlier by the student who offered, “I feel I would havebeen able to gain much more from the class had it been offered in person” (Griffin, 2007).

PEDAGOGICAL LESSONS LEARNED

Central to the pedagogical course design was the incorporation of Chickering and Reisser’s(1993) seven best practices/principles in learning. The first principle recommended the coursedesign should encourage contact between students and the faculty. The course communicationsmodes were chosen to encourage student contact and interaction. The communications modesincluded a discussion board, e-mail, and a chat capability. The discussion board served as the

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primary classroom communications vehicle for posting comments and discussions related to textmaterials, self-assessments, chapter readings and required papers. Each student was required to notonly post a total of sixteen analytical and critical chapter papers, but also post at least two responsesto fellow student’s postings. Students also used the chat and e-mail modes for synchronous andasynchronous communications within their groups to support intra-group interaction andengagement. Student feedback from the two capstone assignments indicated these modes ofcommunications played a significant role in encouraging student engagement in the course. Onestudent offered, “What helped us achieve such cohesiveness was constant good communication. Wewere able to bond with each other, which made our team work well.” A second student describedhow as communications improved, so did engagement,

In the beginning of the semester working together was a little rough. We didn’treally know each other and we were all apprehensive about expressing our truefeelings to one another and giving an honest opinion. As the semester progressedwe were able to work together more and our communication skills improved (Griffin,2007).

Group projects helped support the second principle of developing reciprocity, interaction,collaboration and cooperation among the students. As reported above, students indicated groupprojects were the primary vehicle for gaining practical leadership experience in the course. Thefollowing statements voice what was consistently reported by the students; “Working together withmy group helped me gain a better understanding of leadership and gave me much needed experienceon assuming a leadership role.” And, “Today it is in a collaborative work group that true leadersimmerge. It has become evident that all people have some leadership qualities that can be drawnfrom and used to make the whole group run smoother” (Griffin, 2007).

The third principle encourages active and constructive-oriented learning. Two examples ofactive learning were the rotation of leadership responsibilities and the conduct of the leadershipinterviews within the group projects. The students stated they actively learned leadership bypractical application, “Leadership was learned through group work when each member became aleader at some point, and the other times worked with the leader to accomplish our goals.” Theconduct of three leadership interviews also proved to be an excellent example of active learning.

Specifically, one way I plan to improve my leadership abilities is by learning from the experienced leaders that I interviewed. I feel that one of the most interesting aspects of this course was the vast amount of knowledge I obtained from conductingmy interviews. I was also able to learn from the interviews that were conducted byother students. I found that leaders with more experienced were far more

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understanding leaders and they exerted different leadership styles that weredependent upon the situation (Griffin, 2007).

The fourth principle encouraged faculty to provide prompt feedback. Course gradingexpectations were set in the first week of the course by providing the course syllabus. No studentwas allowed to continue in the class until each had e-mailed the faculty stating they had read,understood and was prepared to comply with the course syllabus. In addition, each student receiveda course grading rubric that explained the grading expectations for the course.

Principle five, emphasize time on task, was supported by setting suspense dates for bothindividual and group related work and assignments. In addition, the instructor managed when andhow long a student could be in an individual module, keeping the student on task, by setting moduletime windows through the instructor controlled Web CT virtual classroom calendar. By controllingstudent module and assignment times the instructor could emphasize time management, a keyleadership skill for these students of leadership.

The communication of high expectations was principle six. This was spelled out in the‘expectations for success’ section of the course syllabus. This section of the course syllabusprovided the students detail on such key topics as grading standards and scale, professionalism,virtual class attendance, and group and individual work. In addition, each student received a coursegrading rubric, for both individual and group assignments, that explained the writing expectationsfor the course. The grading rubrics specifically provided expectations related to paragraphconstruction and mechanics, grammar and spelling, quality of information, sources and citations andstyle of writing.

Lastly, principle seven called for respecting student’s diverse talents and ways of learning.This was facilitated by the content of the course being presented in organized, manageable, andeasily navigated segments known as modules. Student feedback validated that the course structuredid facilitate learning, “It was a well-structured class and it allowed us to work in teams which isa big part of today’s leadership” (Griffin, 2007). The first module was organized to initially insureeach student could successfully work in an on-line course. Then the modules progressively builtupon previously presented leadership theory and practical leadership application. The last modulewas a capstone project in two parts, a group and an individual self-assessment and plan forimprovement.

SUMMARY AND RECOMMENDATIONS

In summation, it was found in MGT 311 that the pedagogical approach did play an importantrole in the overall effectiveness of offering leadership in a totally on-line format. The findings ofthe post-course study (Griffin, 2007) supported the incorporation of Chickering and Reisser’s (1993)guidelines and suggestions for “best practices” in on-line learning. These included: encouraging

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student-faculty interaction through e-mail and discussions, encouraging student cooperation throughcollaborative learning, applying real-world work to course content through the use of group projects,providing prompt, comprehensive feedback by the faculty, recommending completion times for eachmodule, communicating high expectations, and respecting the diverse talents and ways of learningthat each student may bring (Chickering & Ehrmann, 1996; DIIA, 2005).

We offer our experience in developing the on-line version to guide the future developmentof leadership instruction in the on-line learning environment. The expansion of distance educationrequires faculty delivering distance education to re-examine the way teaching and learning takesplace (Palloff & Pratt, 1999). What has evolved in this alternative to the traditional classroom is anew paradigm of teaching and learning. The development of this new paradigm was requiredbecause many of the established assumptions of teaching and learning commonly true in thetraditional classroom do not hold for successful teaching and learning in the distance-educationenvironment. There are several key differences between traditional classroom and distance learningthat include instructor roles, lesson organization, use of technology and the need for collaborativelearning. In making the transition from the classroom to on-line instruction, faculty must concernthemselves with these pedagogical issues (Palloff & Pratt, 1999).

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Hunt, D.M. (2005). Web-based distance learning: substitute or alternative to the traditional classroom: making thedelivery method decision. Online Journal of Distance Learning Administration, 8(3). Retrieved July 31, 2009from http://www.westga.edu/~distance/ojdla/fall83/hunt83.htm

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Simonson, M., S. Smaldino, M. Albright, & S. Zvacek. (2003). Teaching and learning at a distance (Second Edition).Upper Saddle River, NJ: Pearson Education, Inc.

Singleton, E.S., J.R. Hill & M.H. Koh (2004). Improving online learning: student perceptions of useful and challengingcharacteristics. Internet and Higher Education, (7), 59-70.

S u t t o n , L . A . ( 1 9 9 9 ) . I n t e r a c t i o n . R e t r i e v e d O c t o b e r 1 7 , 2 0 0 7 , f r o mhttp://seamonkey.ed.asu.edu/~mcisaac/emc703/leah5.html.

Waits, T. & L. Lewis (2003). Distance Education at Degree-Granting Postsecondary Institutions: 2000-2001, NCES2003-017, Washington, DC: United States Department of Education, National Center for Educational Statistics.

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91


WHAT IS A BETTER PREDICTOR OF SUCCESS IN ANMBA PROGRAM:

WORK EXPERIENCE OR THE GMAT?

Michael H. Deis, Clayton State UniversityReza Kheirandish,Clayton State University

ABSTRACT

The goal of this study was to determine if work experience might be a better predictor ofsuccess than a GMAT score by examining how successful students have been in an MBA programin a suburban metropolitan university. Success in the MBA program was measured by overall GPAfor students completing the program. The study also examined the benefits of offering a GMATWaiver to individuals with significant and leadership experience. Other characteristics, such asage, gender, race, undergraduate GPA and undergraduate upper division GPA were also studied.Preliminary results indicated that significant leadership and administrative work experience werea better predictor than GMAT scores in predicting the overall success of students enrolled in anMBA program. There appeared to be very little correlation between GMAT scores and the overallGPA that students received in the program. The study should be beneficial to universitiesconsidering the criteria on which to place the most emphasis when making admissions decisions.Included in the paper will be a discussion of alternatives to offering the GMAT.

REVIEW OF THE LITERATURE

In a part-time program such as the one being studied in this paper, students are often olderand have more significant leadership and management work experience than students admitted toa traditional MBA program. To maximize the number of admittances and improve the retentionand graduation rates, it is important that those involved with the administration of MBA programsunderstand the likely predictors of graduate student performance to be able to make qualityadmission choices (Sulaiman and Mohezar, 2006).

More and more schools have recognized that the GMAT, including the GMAT AnalyticalWriting Assessment (AWA), should be waived for individuals with significant work experience(Braunstein, 2009). Fish and Wilson (2009) indicated that there also are other differences in factors,such as age, in predicting graduate performance in a part-time MBA compared to a one-year MBAprogram. This should be of particular interest to Clayton State University (CSU), because its 20month is geared towards working professionals.

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Sulaiman and Mohezar (2006) stated that the majority of graduate department admissioncommittees compare total work experience and undergraduate GPA when making an admittancedecision. The article by Sulaiman and Mohezar (2006) gave six hypotheses, one of which stated:“H1: Work experience will predict student performance.” They concluded that, “Those with longerprevious work experience may more readily see the relevance of the management concepts taught.Thus, they would likely perform better than those with less work experience”.

Some leading schools, such as Northwestern University’s Kellogg School of Management,now base their enrollment on undergraduate academic records and work experience (Jones, 2005).As Kellogg’s Julie Jones indicated in a 2005 Business Week article, it does not make a lot of senseto require the Chief Financial Officer of an organization, who had an undergraduate GPA of 3.7 asan accounting major, to take the GMAT. Jones (2005) added that Kellogg places a major emphasison the value and range of work experience that applicants can bring to the program. Many executiveMBA programs now waive the GMAT exam (Gloeckler, 2005). In fact, in 2005, only 12 ofBusiness Week’s top 25 MBA programs required the GMAT. About one-third of the applicants forthe North Carolina Kenan-Flagler Business School opted for a GMAT waiver instead of taking theGMAT (Gloeckler, 2005).

Among the issues that need to be addressed are the standards for granting a GMAT waiver(i.e., not requiring the GMAT) and the requirement of the Analytical Writing Assessment (AWA)when a GMAT waiver is granted. In an MBA program for working professionals, such as the oneat CSU, work experience might be a better predictor of success in the MBA program than theGMAT score or undergraduate work experience (Adams, 2000). Adams (2000) also indicated thatwork experience appears to be a better predictor of success for MBA students than even the GMATor undergraduate GPA. He did so using ANOVA analysis and pointed out that the percentage ofMBA having significant work experience has risen over time.

It must be noted that, based on conflicting evidence about the GMAT as a predictor ofsuccess in MBA programs, the AACSB has stopped requiring GMAT scores for admissions intomany types of MBA programs.

In addition, previous research has also shown that some characteristics such as race andgender might affect the predictive validity of GMAT (Gropper, 2007). David Gropper was theassistant dean and executive director of Auburn’s MBA program when Auburn’s MBA was ranked26th of the nation’s public institutions (Granger, 2005). He found that other factors, such assubstantial career advancement, are better predictors of success in MBA programs. He alsoindicated that factors such as loyalty, stability, and time management may be better predictors ofsuccess in business and therefore in a non-traditional MBA program.

In another significant article, Rogers and Rjntner (2001) stated that the GMAT AnalyticalWriting Assessment (AWA) gave no indication of a writer’s needs, and that the actual essays didnot represent the type of content that MBA students usually had in their writing assignments.Rogers and Rjntner (2001) also pointed out that business school assignments usually concentrate

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on relevant business topics such as employees, co-workers, consumers, investors, and the macrocommunity, whereas the AWA is more of an analytical writing associated with the academicenvironment.

As shown in Table 1 (GMAC, 2008), as the age of applicants increases, the mean GMATscores decrease, indicating that age is apparently an important factor. Many individuals in the CSUMBA program are over the age of 40.

Table 1: Comparison of different age groups on the GMAT

Age Mean GMAT Score

28 – 30 years old 551

31 – 34 years old 539

35 – 39 years old 516

40 – 49 years old 485

(See GMAC, 2008, Table 5)

Further, research indicated that there are usually significant differences, in terms of genderand subgroups, relevant to how well the different groups score on the GMAT. The data shown inTable 2, shown below, must then be considered.

Table 2: Comparison of different age groups on the GMAT in 2007 – 2008

U.S. Subgroup U. S. Mean Total Score Men U.S. Mean Total Score Women

White (non-Hispanic) 560 521

African American 453 418

(See GMAC, 2008, Table 6)

Based on the above review of the literature, there appears to be evidentiary ground for notusing or giving less weight to the GMAT variable when considering admitting decisions. There alsoappears to be evidentiary evidence indicating that other factors, such as race and gender, should beconsidered when reviewing the success of students in an MBA program. The literature appears tosupport the hypothesis.

DESCRIPTION OF DATA

Since Clayton State University began its MBA program with an on-campus cohort in the fall,2007, 112 applicants have been admitted to the program. Sixty-one of those students completedtheir studies by the end of the summer term, 2009. Of those, 31 graduated in the spring, 2009, and

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another 30 graduated in the summer, 2009. Cohort 1 began in the fall, 2007, with 35 students, andthe GMAT was required. Thirty-one students graduated in the spring, and three of those studentshad a 4.0 overall GPA for the entire MBA program. The mean age of students in that cohort was37.

Cohort 2, another on-campus cohort, began in the spring, 2008, with 24 students, and 17completed their studies in the summer, 2009. Of that group, two students had an overall MBA GPAof 4.0. The mean age of that group was 31.

Cohort 3, an off-campus cohort, also began in the spring, 2008, with 14 students. Onewithdrew because of the death of her husband, but 13 completed their studies in the summer of 2009.The mean age of that group was 43. Of those 13, the GMAT was waived for 12 of them based ontheir work experience. The waivers were granted to individuals who had significantly increasingmanagerial responsibilities at a highly responsible level within an organization or to individuals whoown their own businesses. Six of the 12 students receiving GMAT waivers completed theircompleted their studies in the summer, 2009, with a 4.0 overall GPA in the MBA Program. Comparative Descriptive Data for the three cohorts is indicated in Table 3 below.

Table 3: Comparative Data for Students Completing Studies by Summer, 2009

Area Cohort 1 Cohort 2 Cohort 3 Combined Cohorts

N 31 17 13 61

Mean Overall MBA GPA 3.68 3.72 3.88 3.73

Overall Undergraduate GPA 3.17 3.19 2.8* 3.1*

Upper Division Undergraduate GPA 3.41 3.38 2.85* 3.29*

GMAT Mean 449 431 470** 444**

Race (# of white students) 19 9 10 38

Gender (# of female students) 23 12 5 40

Age (at the start of MBA program) 37 31 43 37

*Undergraduate overall and upper level GPA for one student was not available**In cohort 3, GMAT scores for all students with GMAT waiver except one were not available. The GMAT scorefor that student was older than 5 years old and therefore was not considered for the analysis but is used incalculating the mean.

ANALYSIS

Using a sample of the 61 recent graduates, the authors did a statistical analysis to determine(a) if work experience was a better predictor of success in the MBA program than GMAT scores and(b) what other variables might predict success in the program. The authors thus studied the effectsof characteristics such as gender, race, and age on success, as measured by overall graduate GPA.

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For cohorts 2 and 3, which began at the same time, took the courses in the same sequence,followed the same curriculum, and were taught by the same faculty, the only difference was thatGMAT scores were required for cohort 2 and GMAT waivers were available for students in cohort3. This will permit the authors to compare the two cohorts using two sample tests of our hypothesis.One would prefer to look at the regression analysis of the effect of GMAT on MBA overall GPAby adding GMAT waiver dummy variable and slope dummy. However, due to absence of GMATscores for those who used GMAT waiver, that analysis is not possible. Hence, the authors used thet-test function in Microsoft Excel to compare the mean of the two samples: The one with GMATwaiver and the one without. Here is the hypothesis:

(1)1 2

1 2

: : >

HoHa

m mm m

ì £ïïíïïî

where m1 is the MBA GPA mean for the MBA students with GMAT waiver and m2 is the MBAGPA mean for the MBA students without GMAT waiver. The p-value for the test is very small(0.000238) which means we strongly reject the null hypothesis that those with GMAT waiver doworse than those without GMAT waiver. This also indicates that we have strong evidence that thosewith GMAT waiver do significantly better than those without GMAT waiver.

After finding out that the group of students with GMAT waiver did better in their MBAstudies - as measured by overall MBA GPA – the authors tried to answer the following question:For the students without GMAT waiver, did GMAT score predict their success and was there anydifference in their success based on their overall undergraduate GPA, age, race, or gender? Toanswer this question authors ran the following regression:

(2)0 1 2 3 4 5MBA GPA GMATTotalScore UndergradGPA AgeatStart White Femaleb b b b b b= + + + + +

where variables White and Female are two dummy variables with values equal to one when thestudent’s race and gender are white and female, respectively, and zero otherwise. The results of thisregression analysis are reported in Table 4:

The adjusted R2 indicates that about 20% of the variation in dependent variables can beexplained by variations in independent variables. The coefficients for all variables except race(dummy variable White) are insignificant. When authors examined simple regression model withonly GMAT score as independent variable the adjusted R2 was only 3% and coefficient for GMATscore was insignificant. This suggests little or no connection between GMAT scores and success inMBA program as measured by MBA GPA..

A closer look at scatter plot of MBA GPA vs. GMAT scores also suggests that there is noconnection between MBA success and GMAT scores (Figure 1). There is no evidence that MBA

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GPA as a measure of success and GMAT are linearly related. Figure 2 depicts the plot of residualsof the regression model against the predicted values of MBA GPA.

Table 4: Determinants of Students’ MBA GPA

Regression: MBA GPA b0 b1 b2 b3 b4 b5

constantGMAT Total

ScoreUndergrad

GPA Age at start white female

Coefficient 3.15566 -0.00003 0.14513 -0.00227 0.16960 0.10584

std error of coef 0.32729 0.00051 0.09791 0.00353 0.07066 0.07699

t-ratio 9.6418 -0.0531 1.4823 -0.6438 2.4003 1.3747

Significance 0.00% 95.79% 14.55% 52.31% 2.08% 17.63%

beta-weight -0.0079 0.2284 -0.0868 0.3316 0.1889

standard error of regression 0.227936757

R2 28.83%

adjusted R2 20.56%

number of observations 49

residual degrees of freedom 43

t-statistic for computing

95%-confidence intervals 2.0167

Figure 1: Scatter plot of MBA GPA vs. GMAT scores

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Figure 2: Scatter plot of MBA GPA vs. GMAT scores

SUMMARY AND REFLECTION

Although the study involves a small number of individuals, it appears that work experienceis a better predictor of the overall GPA in an MBA program than the GMAT exam. The CSU studyconfirms this, as did the study by Gropper (2007). The CSU study confirmed that there appears tobe evidentiary grounds for not using or giving less weight to the GMAT variable when consideringadmitting decisions. This initial study appears to indicate that this university must thoroughlyconsider the positive effects of considering work experience as it relates to overall performance inan MBA program.

The university must still, however, have a means of knowing the skills of students withsignificant work experience. One possible solution would be to offer a provisional acceptance forthose qualifying for GMAT waivers, and to then require an in depth writing assignment in the firstcourse that the students took in an MBA program. By offering provisional entry, MBA candidateswill be given the chance to prove they can perform at the MBA level. Since the GMAT is possiblynot as good a predictor as work experience, having an in depth writing assessment in the first MBAcourse would still identify any writing weaknesses that students might have. MBA students takelearning seriously and actively seek tutorial help when needed. By having the in depth writingassignment, students could still be evaluated on their writing skills and given additional help.

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REFERENCES

Adams, A. & Hancock, T. (2000). Work experience as a predictor of MBA performance. College Student Journal, 34(2).

B r a u n s t e i n , A . ( 2 0 0 9 ) . P r e d i c t i n g p e r f o r m a n c e i n a n M B A p r o g r a m .http://www.iaes.org/conferences/past/philadelphia_52/prelim_program/a20-1/braunstein

Fish, L. A., and Wilson, F., S. (2009). Predicting performance of MBA students: Comparing the part-time MBA programand the one year program, College Student Journal, 43 (1).

GMAC ( 2008). Profile of Graduate Management Admission Test candidates: Five-year summary (2003 – 2008).Graduate Management Admission Council, 1600 Tysons Blvd, Suite 1400, McLean, VA 22102.

Granger, David M. (2005). Auburn MBA program ranked 26th among public institutions by Forbes. Auburn News.9/6/05. http://www.ocm.auburn.edu/news_releases/forbesmba

Gropper, Daniel M. (2007). Does the GMAT matter for executive MBA students? Some empirical evidence. Academyof Management Learning & Education, 6(2), 205 – 216.

Jones, Julie C. (2005). Looking beyond the GMAT. Business Week. August."http://www.businessweek.com/magazine/content/05_32/b3946112"http://www.businessweek.com/magazine/content/05_32/b3946112

Rogers, P., & Rjntner, J. (2001). Analytical tools to facilitate transitions into new writing contexts: A communicativeperspective. The Journal of Business Communication. 38(2), April, 112 – 152.

Sulaiman, A., and Mohezar, S. (2006). Student success factors: Identifying key predictors. Journal of Education forBusiness. July/August, 2006, 328 – 333.

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FACTORS INFLUENCING STUDENT PERFORMANCEIN THE INTRODUCTORY MANAGEMENT SCIENCE

COURSE

Kelwyn A. D’Souza, Hampton UniversitySharad K. Maheshwari, Hampton University

ABSTRACT

The introductory management science course is a core requirement for many undergraduatestudents majoring in business. In general, it is considered to be a challenging course having highwithdrawal and failure rates. The purpose of this paper is to examine factors that influence theperformance of students in the introductory management science course. To evaluate these factors,a study was conducted over a two-year period covering around 300 students from business andother majors at Hampton University, Hampton, Virginia. Several independent variables related tostudent demographics, course structure, instructional methods, student motivation and effort,student aptitude and application, and student preparation were considered. Nine of these variablesshowed some significant relationship with the performance. Furthermore, a multiple regressionmodel was constructed using stepwise method. Four independent variables were included in thefinal regression model: current class grade point average, average homework score, courseutilization ratio, and completion of pre-calculus prerequisite. The final multiple-regression modelexplained around 51% of the variation. The results emanating from this paper could assist in re-designing and delivery of management science course material.

INTRODUCTION

There is a growing concern about the poor performance of undergraduate students in theintroductory management science course, which is a core requirement in most business degreeprograms and a prerequisite for advanced courses. At Hampton University, business students arerequired to earn a C grade or higher in this course (Quantitative Methods) to fulfill graduationrequirements. The number of students not meeting this requirement in their first attempt is high,with approximately one-third of the students earning less than a C grade, thus having to repeat thecourse. This exerts a financial strain on the students, lowers overall GPA, delays graduation, andcauses overcrowding of management science classes.

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The main motivation behind this study is to establish the underlying causes of higher failurerate in this course. The literature review shows that statistical techniques are extensively appliedto model student academic performance in several courses. A number of researchers used statisticalmodels to study factors influencing performance in accounting, economics, and finance courses.However, there is a lack of application of similar statistical techniques to analyze performance inmanagement science courses. A small number of recent studies have been reported which analyzestudents’ performance in such courses. Furthermore, these studies do not necessarily agree on thereasons for poor performance. Grossman (2001) provided several reasons for poor performanceranging from student lack of preparation to ineffective course design. Brookshire and Palocsay(2005); Peters et. al. (2002); and Mukherjee (2000) have studied management science courses andarrived at somewhat different causes of poor performance. This indicates that further investigationmay be necessary to understand the root causes of poor performance and recommend correctivemeasure to improve students’ performance in the management science course.

This paper attempts to highlight a wide range of significant factors which could beresponsible for the poor performance in the management science course (Quantitative Methods)offered by the Department of Management at Hampton University. The study was conducted overtwo academic years covering around 300 students in 10 sections taught by a single instructor usinga standardized course syllabus and grading criteria. In order to protect the confidentiality of student,personal identities were not disclosed and the study was approved by the University’s InstitutionalReview Board (IRB).

The study initially considered a wide range of independent variables that could possiblyinfluence the performance. Preliminary statistical tests resulted in elimination of the non-significantvariables. A multiple regression model was developed relating nine independent variables to studentperformance measured by the simple average of tests and final examination scores. A final multipleregression model was created using stepwise method resulting in four independent variables as apredictor for student performance. These four variables were current class grade point average,average homework score, course utilization ratio (ratio of total hours earned by total hoursattempted), and completion of precalculus prerequisite.

LITERATURE REVIEW

A number of studies have been conducted worldwide to assess the students’ performance invarious introductory undergraduate courses. The literature does not agree on a set of factors whichinfluences the performance of the students in introductory college level courses. Certain factors arefound to influence the performance at some institutions while not at others. A review of theliterature highlighting the numerous factors that could possibly influence performance follows.

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Student Demographics (major, age, gender, and race)

Most business majors are required to complete the introductory management science course.Students registered in a major that includes the introductory course are expected to perform betterthan students from other majors. Brookshire and Palocsay (2005) found significant difference inmean quality points for the management science course among students from different majors,although no conclusion was drawn for any particular major.

It is commonly believed that older students have a higher performance due to increased levelof maturity and responsibility. Eikner and Montondon (2001) found that older nontraditionalstudents had a higher success rate in an Intermediate Accounting I course. A highly significantpositive relationship existed between age and grade in a financial accounting course (Munro, 2001).Age did not impact the performance in an introductory management accounting course (Monem,2007) and among accounting graduating students (Al-Rashed, 2001). A study on mostly traditionalstudents ages 19 to 23 taking an introductory management science course found no significantdifference in performance (Brookshire and Palocsay, 2005).

An increase in percentage of female student attending universities has drawn the interest ofresearchers studying the relationship of gender on performance. The performance of males washigher in an introductory information systems course (Kruck and Lending, 2003). Monem (2007)found males marginally outperform females in an introductory management accounting course. Thefemale students in an introductory accounting course studied by Sugahara and Boland (2006)performed significantly better than males. Gracia and Jenkins (2003) and Tho (1994) found femalesoutperform males in accounting and finance courses. A similar study found females outperformedmales in first year accounting and auditing courses, while no gender difference was found in thefinal year courses (Gammie et.al. 2003). Graduating female students performed better than malestudents in the accounting and business programs (Alfan and Othman, 2005). Other researchershave found no significant difference in the performance of male and female students (Brookshireand Palocsay, 2005; Eikner and Montondon, 2001; Al-Rashed, 2001).

The study of influence of race on performance has produced inconclusive results. Eikner andMontondon (2001) included the race variable (minority, non-minority) in their final regressionmodel, but found it was not significant at conventional levels. While, Alfan and Othman (2005)found student’s performance in accounting and business programs is dependent on their race.

Course Structure (class size, duration, timing, and length)

The introductory undergraduate courses are generally taught in large lecture classes, atdifferent day times, and varying class duration and semester length. The effect of class size onperformance has long been a topic of debate in the school systems with no conclusive results(Salvin, 1989). At the college level, introductory accounting courses taught in large lecture sections

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had no significant impact on performance (Eskew and Faley, 1988). The performance of studentsin an introductory finance course was not affected by class size, duration of 75 or 150 minutes, andtime of the day time class meetings, but students in evening classes performed lower than their daytime counterparts (Wilson, 2002). According to Devadoss and Foltz (1996), students preferred 50minute classes held on Monday, Wednesday, and Friday. In a larger study covering a wide subjectarea, Gibbs et. al., (1996) confirmed the hypothesis that students would perform less well in largerclasses. Ewer et. al., (2002) found that students perform equally well in a four week and 16 weeksemester length.

Instructional Methods (instructor status and presentation style)

The course instructor plays a major role in student learning. College level teaching is a skillacquired through education and years of experience. Many introductory level courses are taught byadjunct or part-time faculty. Contrary to the general belief that courses taught by full-time tenuredfaculty would result in a higher performance, Wilson (2002) found that student taught by lecturershad a higher performance than those taught by tenured and tenure track faculty. Reporting on theperformance in the introductory management science course, Brookshire and Palocsay (2005) founda significant difference in the performance of students taught by five different instructors, but furtherinformation of instructor status was not available. The use of audiovisual aids is helpful especiallyin large lecture classes. Powerpoint is a common aid used by many instructors from various fieldsof study, and is used extensively by conference participants. Its real effectiveness in improvingperformance is debatable. Most students say it helps in following the lecture while keeping theinstructor focused on the topic. A study by Sugahara and Boland (2006) showed that student whoprefer Powerpoint lectures scored lower on the final examination as compared to students who preferthe traditional whiteboard presentation.

Student Motivation and Effort (attendance, homework, and quizzes) A motivated student will attend class regularly and participate in the assignments. By simply

recording attendance, Shimoff and Catania (2001) found an increase in class participation andcorresponding increase in overall academic performance. A study conducted by Devadoss and Foltz(1996) provides strong empirical evidence of the positive impact of class attendance onperformance. Marburger (2001) has reported that performance in the Principles of Microeconomicsexamination was significantly affected due to absenteeism.

The role of homework on the performance of school grades has been studied extensively(Trautwein and Köller, 2003). At the college level, researchers have supported the usefulness ofhomework as a supplement to classroom learning and in improving performance especially inintroductory courses. Sasser (1981) found the performance of college students in a freshman algebracourse receiving homework was significantly greater than those not receiving homework. Kruck

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and Lending (2003) found effort/motivation, measured by homework scores was significantly relatedto performance. According to Neilson (2003), the effectiveness of homework is related to timeconstraint. When there is no time constraint, it can be beneficial but its effectiveness lessens undertime constraints especially experienced by working students. In an introductory operationsmanagement course, Peters et. al., (2002) found grading homework did not affect examinationperformance on quantitative questions but contributed significantly to performance on non-quantitative questions. The graded homework returned to students and once again reviewed beforea test has shown to improve performance (Mukerjee, 2000).

The number of quizzes taken was significantly related to examination performance (Eskewand Faley, 1988). The use of random, extra credit quizzes increased attendance by about 10%, andimproved examination performance (Wilder et. al., 2001). A study by Haberyan (2003) foundweekly quizzes did not improve student performance in a college-level general biology course, butstudent preferred quizzes as it helped in the preparation for examinations.

Student Aptitude and Application (SAT, and current class GPA)

Currently, some universities are debating the requirement of SAT scores as part of theapplication requirements, and making it optional for applicants with high GPA and class ranking(Daily Press, 2007). Eskew and Faley (1988) reported that SAT (math and verbal) score contributedsignificantly to student performance in the introductory accounting course. According to Brookshireand Palocsay (2005), the SAT math score has significant bivariate correlation with performance inthe management science course. The SAT scores predicted academic performance for male studentsbut not for female students (Kruck and Lending, 2003). The SAT math and verbal scores hadsignificant influence on immediate accounting tests (Bernardi and Bean, 2002).

The influence of current class GPA on performance has been widely studied by researchers.Gracia and Jenkins (2003) found previous GPA earned had a significant effect on current GPA inthe accounting and finance program. Kruck and Lending (2003) found a significant relationshipbetween collegiate GPA and overall performance in an introductory information systems course.Eikner and Montondun (2001) concluded that college GPA to date was significantly related toperformance in an intermediate accounting course. The GPA earned at the end of sophomore yearstrongly influenced performance in the complete accounting program (Al-Rashed, 2001). Theoverall GPA (excluding management science, calculus, and statistics course grades) was found tobe most significantly related to the grade earned in the introductory management science course(Brookshire and Palocsay, 2005).

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Student Preparation (prerequisites, transfer, and course repetition)

The prerequisite courses are generally scheduled during the freshman/sophomore year toprepare students for advanced courses. The usefulness of these courses has often been questioned.Bernardi and Bean (2002) have found that performance in Intermediate Accounting-I has a positiveimpact on the performance in Intermediate Accounting-II suggesting the importance of introductorycourses as an indicator of success in more advanced courses. This was corroborated by Al-Rashed(2001) who found grades in introductory accounting and finance courses had a positive correlationwith performance of graduating accounting students. The prerequisites generally required for anintroductory management science course are one semester each of calculus and statistics.Brookshire and Palocsay (2005) found performance in the management science course wassignificantly correlated with quality points in the calculus and statistics courses. Eskew and Faley(1988) found college-level math and statistics courses do improve performance in introductoryaccounting course. Eikner and Montondon (2001) found that performance in the first intermediateaccounting course was significantly related to the grade in the first accounting principle course.Surprisingly, Kruck and Lending (2003) found taking a similar course or programming classes didnot improve the performance in the information systems course. Core courses taken by businessstudents did not have a strong positive relationship with the final cumulative GPA (Alfan andOthman, 2005).

Often, prerequisite courses are transferred from high school AP program or from previouslyattended institutes of higher learning. Munro (2001) studied the performance of students in aFinancial Accounting course who were granted transfer credits for a prerequisite first levelaccounting course. The results indicate that students who completed the prerequisite course in-house performed better than those who received transfer credits from other institutes. Eikner andMontondon (2001) studied the performance of student who transferred courses from other collegesand found no significant difference in performance between transfer and traditional students, andthose repeating a course performed marginally better.

Multivariate Analysis

The relationship between the student performance and explanatory factors has beenestablished in the past by researchers using multivariate analysis (Eskew and Faley, 1988; Millerand Westmoreland, 1998). This approach has been replicated by researchers from differentdisciplines to correlate multi-factors with performance. Kruck and Lending (2003) developed amultiple regression model that used five independent variables to predict grades in an introductoryinformation science course. Eikner and Montondon (2001) identified eight independent variablesas potential performance indicators in the first intermediate accounting course and found three tobe significant: college GPA, grade in the first accounting principle course, and age. Garcia and

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Jenkins (2003) used multiple regression and principal component analysis to study the impact ofaround 20 independent variables on performance of a degree program in accounting and finance andfound six were significant in explaining the variation in current performance. A multiple regressionmodel was developed by Al-Rashed (2001) that related the final GPA of accounting students to 11independent variables. After conducting a stepwise multiple regression analysis, Al-Rashed (2001)found a single variable (GPA) most significant, while the others had lesser degree of significancein predicting performance.

A few multivariate analyses have been conducted in the field of management science.Brookshire and Palocsay (2005) applied multiple regression analysis to determine significant factorsthat impact performance of students in an introductory management science course and foundoverall academic performance (GPA) had the strongest correlation with performance, while othervariables included in the model (SAT math score, prerequisites, major, and instructor) had a lessersignificance on the performance.

RESEARCH DESIGN AND RESULTS

The review of previous research across various fields identified a range of factors that couldinfluence the academic performance in introductory business courses. As expected, the researchersdiffer on which factors are more important for the students’ academic success. Furthermore, eachresearch study considered different set of factors and used variety of measurements to assess theacademic performance. In this study, we considered several previously reported along with somenew factors together to investigate our basic research question “What factors determine academicperformance in an introductory management science course?” Six different set of independentvariables were considered that included student demographics, course structure, instructionalmethods, student motivation and effort, student aptitude and application, and student preparation.These sets are discussed later in this section.

The Course Details and Sample Size

The course studied for this research was a three credit hour introductory management science(Quantitative Methods) course required by all business majors and used as an elective by studentsfrom other majors. This sophomore level course is sequenced during the fourth semester andrequires calculus and statistics prerequisites. The classes were taught by a single tenured professoron Monday, Wednesday, and Friday between 8:00 AM and 11:00 AM. A common course syllabusand grading scale was used covering deterministic and probabilistic models outlined in the samplecourse design by Borsting et. al. (1988). Powerpoint presentation was used as a teaching tool in allsections and made available electronically to students. The final score was complied as a weightedsum of three tests (45%), final examination (20%), homework (10%), quizzes (10%), class project

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(10%), and attendance/participation (5%). A course grade was assigned according to theUniversity’s grading system. The tests and final examination consisted of a combination ofmultiple-choice questions (30%) and numerical problems (70%). Homeworks and quizzes wereassigned at the end of each chapter and were graded and returned back to students. The class projectdemonstrated an application of a management science technique covered during the course. Theattendance/participation score was computed based on the number of unexcused absences.

The course was studied over a two-year period covering 333 students in 10 sections taughtduring the fall 2005 to spring 2007 semesters. Out of 333 students, 297 were assigned a letter gradefrom A through F. The remaining 36 students (around 11%) withdrew from the course, or did nottake the final exam.

Preliminary Statistical Analysis

The methodology follows the approach of Eikner and Montondou (2001). The variablesidentified in the literature review were analyzed separately in relation to performance using the t-test, ANOVA, and/or simple regression, and significant variables were included in the multipleregression model. Instead of using the final grade for performance measure as suggested by Eiknerand Montondou (2001), or the final examination score (Sugahara and Boland, 2006), this study usedthe simple average of the three tests and final examination scores (AVGT). The tests and finalexamination, from which the AVGT is computed, are conducted in class under supervision andhence, expected to reflect the true performance of students. Trautwein and Köller (2003) have alsorecommended the use of standardized achievement tests instead of grades to measure theperformance of students.

Student Demographics (major, age, gender, and race)

The student population included largely business majors along with a few non-businessmajors. An ANOVA test showed no significant difference (F=1.638, df=296, p=.1499) in AVGTfor the different majors presented in Table 1.

Most of the students in the study group were African-American sophomores or juniorsresiding on campus. Since the sample was largely homogenous with respect to age and race, thesevariables were not analyzed further. Table 2 provides a distribution of males and females in thestudy group. The females outnumber males (54% versus 46%) reflecting a national trend of higherenrollment of female college students. The AVGT scores for female and male differ significantly(t = 2.621, p = .009) suggesting that female students’ performance was significantly better than malestudents in the course.

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Table 1. Student Major Groups.

Semester Accounting Economics &Entrepreneurship

Finance Management Marketing Others

Spring 2007 10 6 9 18 20 1

Fall 2006 6 4 6 21 11 2

Spring 2006 17 10 14 21 36 3

Fall 2005 8 8 12 34 20 0

Total 41 28 41 94 87 6

AVGT 77.91 76.04 81.00 76.74 79.59 76.50

Table 2. Gender Detail

Gender Sample Size % Mean AVGT Std. Dev.

Female 161 54% 79.82 8.35

Male 136 46% 77.00 10.15

Total 297 100% 78.53 9.31

Based on the preliminary statistical analysis of student demographics, only the independentvariable GENDER is included in the multiple regression model.

Course Structure (class size, duration, timing, and length)

The Table 3 presents a summary of descriptive statistics for each course section. Due tolimited data sets, the class size was divided into two groups: small class (# 30 students) and largeclass (> 30 students). The AVTG for small and large classes is not significantly different (t = -.994,p = .321). All the classes were held on Monday, Wednesday, and Friday at 8:00 AM, 9:00 AM,10:00 AM, and 11:00 AM for a duration of 50 minutes each. The t-test for sample pairs of differentclass meeting timings show no significant difference (t = -0.009, p = 0.993 to t = -1.594, p = 0.118)in the AVTG. Similarly, there was no difference found between Fall and Spring semesters’ AVTG(t= -.1965, p=.8442). The class length and semester duration variables could not be tested as all 10sections considered in the study met for 50 minutes each in the regular 15-week semester.

Based on the preliminary statistical analysis of course structure, none of the independentvariables in this set were significant; hence none of these variables were included in the multipleregression model.

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Table 3. Class Size and Timing

Section Semester Timing Class Size Mean AVGT Std. Dev.

1 Spring 2007 8:00 AM 31 78.133 7.016

2 Spring 2007 9:00 AM 33 77.508 11.563

3 Fall 2006 8:00 AM 20 77.981 10.457

4 Fall 2006 9:00 AM 30 77.846 10.226

5 Spring 2006 8:00 AM 33 79.311 7.725

6 Spring 2006 9:00 AM 31 80.00 7.539

7 Spring 2006 11:00 AM 37 79.980 10.617

8 Fall 2005 9:00 AM 27 76.111 8.113

9 Fall 2005 10:00 AM 27 76.778 7.673

10 Fall 2005 11:00 AM 28 80.839 10.987

Instructional Methods (instructor status, presentation style, and textbook)

All the sections were taught by a single tenured professor using Powerpoint presentation.The presentations were available electronically to students through the University website. Since,all sections were taught by same professor using similar presentation style, the instructor status andpresentation style variables could not be tested. The prescribed text book for the course waschanged in the Fall 2006. A t-test for the two sample courses using the old book in Spring 2006 andthe new book Spring 2007 showed no significant differences in AVGT (t = - .639, p = .525.)

Based on the preliminary statistical analysis of instructional methods, none of theindependent variables in this set were significant; hence none of these variables were included inthe multiple regression model.

Student Motivation and Effort (attendance, homework, and quizzes)

Class attendance was required and constituted part of the final grade. A simple regressionanalysis conducted separately for the number of days absent and percentage of days absent showeda significantly high (p<.001) relationship on the AVGT. The percentage of days absent had astronger relationship (r-square = 0.09) with AVGT.

Homework was assigned at the end of each chapter to strengthen learning of conceptual andquantitative materials. All homework were collected, graded by the instructor, and returned backto the students. A simple regression analysis conducted separately for the number of homeworksubmitted, percentage of homework submitted, and the average homework score showed a

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significantly high (p<.001) relationship with AVGT. The average homework score had a strongerrelationship (r-square =.238) with AVGT.

A short quiz followed the completion of each chapter. These were completed outside theclassroom and were collected during the next class meeting, graded by the instructor, and returnedback to the students. A simple regression analysis conducted separately for the number of quizzessubmitted, percentage of quizzes submitted, and the average quiz score showed a significantly high(p<.001) relationship with AVGT. The average quiz score had a stronger relationship (r-square=.146) with AVGT.

As expected, all the motivation and effort variables were significant in the preliminarystatistical analysis. Hence, the independent variables, percent of days absent (%ABS), averagehomework score (AHW), and average quiz score (AQZ) were included in the multiple regressionmodel.

Student Aptitude and Application (SAT, current class GPA, and course utilization ratio)

As reported in many studies, the SAT scores are a good predictor of the performance duringfreshmen year of college. Since, the Quantitative Methods course is a sophomore level course, SATscores were not included in this study. According to the business curriculum outline, all studentsmust enroll in the Quantitative Methods course preferably during their sophomore year aftercompleting at least 45 semester credit hours. An analysis of average hours attempted (96.65 hours)and the average hours earned (89.29 hours) up to completion of the course indicates that studentswere enrolling in this course much later in their curriculum, some even during their final semester.A number of students earned transfer credit hours that are included for total curriculum requirementbut not included in the hours attempted and hours earned for class GPA computation. Hence, it wasdecided to compute the course utilization ratio of total hours earned to total hours attempted(HE/HA). This average value of HE/HA for this study was = 0.937 indicating a loss of hours dueto withdrawal or failing grades. The current class GPA (including the Quantitative Methods course)and the course utilization ratio are reflective of the student’s aptitude and application. A simpleregression conducted separately for the current class GPA and course utilization ratio on AVGT,showed the former had a significant relationship (r-square =.404, p<.001) and the latter had asignificant relationship (r-square = .119, p<.001). The GPA and course utilization ratio hassignificant relationship with AVGT indicating that higher values should lead to better performance.Hence, current class GPA (GPA) and course utilization ratio (HE/HA) were included in theregression model, and the SAT score was not included.

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Student Preparation (prerequisites, transfer, and course repetition)

The curriculum requires two prerequisite courses in calculus and statistics to be completedprior to enrolling in the Quantitative Methods course. The AVGT for students who completed theCalculus and Statistics prerequisites earning a passing grade were significantly higher than studentswho did not complete the prerequisites (Table 4). The completion of Precalculus Mathematics Icourse which is a prerequisite for the Calculus as well as Statistics courses also had a significantimpact on the AVGT.

Table 4. Statistical Test for Prerequisites

Prerequisite Completed Not Completed Significance

Calculus (P1) Mean AVGT = 80.34Std. Dev. = 8.83

Mean AVGT = 73.86Std. Dev. = 8.94

t=-5.626p<.001

Statistics (P2) Mean AVGT = 79.40Std. Dev. = 9.11


t=-3.806p<.001

Precalculus Mathematics I (P3) Mean AVGT = 79.37Std. Dev. = 8.66


t=-3.534p=.001

The School allows students to transfer non-business course credits (not quality points)completed at any accredited institution of higher learning. The focus of this research was onstudents who obtained transfer of the prerequisite MAT 130 - Calculus. There was no significantdifference (t=-.821, p=.417) in AVGT between students who completed the calculus course oncampus or at another institution. This contradicts results of Munro (2001).

Student repeating the course either withdrew from the previous course or received a lowergrade than is necessary for their curriculum. There was no significant difference (t=1.186, p=.236)noted in AVGT between repeat and first time students. A similar analysis by Eikner and Montondon(2001) found marginal difference in performance.

Based on the preliminary statistical analysis of student preparation, the independent variablesfor completion of all direct and indirect prerequisites: Calculus (P1), Statistics (P2), and PrecalculusMathematics I (P3) were included in the multiple regression model.

Multiple Regression Analysis

Of the 22 independent variables analyzed by preliminary statistical methods, nine significantindependent variables were included in the following multiple regression model.

AVGT = $0 + $1GPA + $2GENDER + $3%ABS + $4AHW + $5AQZ + $6HE/HA + $7P1 + $8P2 + $9P3 + ,

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Dependent variable

AVGT: the simple average of three tests and final examination scores.

Independent Variables

GPA: a continuous variable representing the current class GPA up to completionof the Quantitative Methods course.

GENDER: a dummy variable, Male = 1, Female = 0.%ABS: is a continuous variable representing the percentage of days absent (excused

and unexcused) during the semester.AHW: a continuous variable representing the average homework score out of 10.AQZ: a continuous variable representing the average quiz score out of 10.HE/HA: a continuous variable representing course utilization ratio (total hours earned

by total hours attempted) up to completion of the Quantitative Methodscourse.

P1: a dummy variable for Calculus prerequisite. Completed = 1, not completed= 0.

P2: a dummy variable for Statistics prerequisite. Completed = 1, not completed= 0.

P3: a dummy variable for Precalculus Mathematics I prereq. Completed = 1, notcompleted = 0.

An analysis was conducted to determine the equation of the multiple regression model thatbest fits the data. The multiple regression results for the nine variables are shown in Table 5. Thecomputed value of F = 34.214 and the P-value < 0.001 indicates that some of the independentvariables have the ability to explain the variation in AVGT.

As shown in Table 5, only four out of nine variables have significant contribution to theregression model. It clearly shows that contribution of some variables is mostly explained by theother variable, as the regression model only considered variables which independently showedsignificant relationship with AVGT. For example, Precalculus Mathematics I (P3) is a perquisitefor both Statistics (P2) and Calculus (P1). And the regression model shows that completion of P3explained most of the variability as compared to the prerequisites P1 and P2. It is possible that anumber of students who completed P3 had also completed P1 and P2 courses. Furthermore, acorrelation matrix (Table 6) was developed showing the coefficient of correlation between pairs ofindependent variables. All the variables except GENDER and P2 appear to have a medium to strongcorrelation with AVGT. GPA has the strongest relationship and GENDER and %ABS havenegative signs indicating an expected inverse relationship. A check for multicollinearity was

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conducted to determine if there was any correlation among the independent variables. With theexception of HE/HA and GPA (0.752), all the coefficients are between –0.70 and 0.70 and shouldnot cause a correlation problem (Lind et. al., 2006).

Table 5. Multiple Regression Results

Test of Significance of the Regression Model

Coefficient of multipledetermination R2 = 0.5176.

R-square =0.518.

ANOVAF = 34.2141, df = 296Significance < 0.001.

StandardError =6.5666

N = 297

Test of Significance of the Intercept and Individual Variables

Independent Variables Coefficients t Statistics P-value Significance

Intercept 72.329 10.81 <0.001 Yes

GPA 13.157 10.53 < 0.001 Yes

GENDER -1.118 -1.41 0.1594 No

%ABS -1.482 -0.31 0.7564 No

AHW 1.356 4.49 < 0.001 Yes

AQZ -0.471 -1.07 0.2841 No

HE/HA -42.541 -5.17 < 0.001 Yes

P1 0.758 0.70 0.4846 No

P2 1.285 1.17 0.2452 No

P3 2.916 2.05 0.0416 Yes

Table 6. Correlation Matrix

AVGT GPA GENDER %ABS AHW AQZ HE/HA P1 P2 P3

AVGT 1

GPA 0.636 1

GENDER -0.155 -0.13 1

%ABS -0.301 -0.35 0.210 1

AHW 0.488 0.482 -0.147 -0.527 1

AQZ 0.382 0.486 -0.088 -0.519 0.676 1

HE/HA 0.345 0.752 -0.160 -0.354 0.391 0.384 1

P1 0.313 0.356 -0.049 -0.111 0.147 0.184 0.248 1

P2 0.216 0.268 -0.123 -0.054 0.098 0.127 0.228 0.223 1

P3 0.248 0.159 -0.065 -0.147 0.131 0.097 0.088 0.540 0.099 1

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The multiple regression output data was further analyzed by plotting the residuals versuspredicted AVGT for each set of inputs. The scatter plot (Figure 1) shows the spread of residualsremains mostly constant except for few outliers at the lower AVGT values, thus fulfilling thehomoscedasticity condition.

Stepwise Regression

As described in the earlier section, not all nine variables are contributing significantly tomultiple regression model. The stepwise multiple regression (SPSS, Inc., 2003) was used to findthe better and concise regression model from the set of independent variables under consideration.The multiple regression model summary is shown in Table 7 along with the variable coefficients(Table 8).

Table 7. Multiple Regression Model Summary

Model Predictors R R -SquareAdjusted R

SquareStd. Error of the

Estimate

1 GPA 0.636 0.404 0.402 7.198

2 GPS, AHW 0.669 0.447 0.443 6.945

3 GPA, AHW, HE/HA 0.702 0.492 0.487 6.666

4 GPA, AHW, HE/HA, P3 0.713 0.508 0.501 6.574

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Table 8. Variable Coefficients

Model Variable Unstandardized CoefficientsStandardizedCoefficients T Sig.

B Std. Error Beta

1 (Constant) 46.531 2.300 20.231 .000

GPA 11.498 .813 .636 14.148 .000

2

(Constant) 43.750 2.294 19.071 .000

GPA 9.436 .895 .522 10.545 .000

AHW 1.200 .251 .237 4.784 .000

3

(Constant) 70.782 5.733 12.347 .000

GPA 13.719 1.200 .759 11.429 .000

AHW 1.261 .241 .249 5.231 .000

HE/HA -41.998 8.223 -.323 -5.107 .000

4

(Constant) 67.847 5.734 11.832 .000

GPA 13.303 1.191 .736 11.165 .000

AHW 1.213 .238 .239 5.092 .000

HE/HA -40.721 8.120 -.313 -5.015 .000

P3 3.666 1.202 .127 3.050 .003

The final multiple regression model (Mode 4) is:

AVGT = 67.847 + 13.303GPA + 1.213AHW – 40.721HE/HA + 3.666P3.

DISCUSSION

Out of nine independent variables in the multiple regression model, four appear to besignificant in explaining the variation in the measure of performance in the Quantitative Methodscourse. The current class GPA is the strongest predictor of performance. Students who have a highcurrent class GPA have the aptitude to perform well. This matches the results of recent researchacross different fields (Brookshire and Palocsay, 2005; Kruck and Lending, 2003; Gracia andJenkins, 2003; Al-Rashed, 2001; Eikner and Montondun, 2001).

Homework plays an important role in understanding the course material presented in theclass and contributes 10% of the overall grade. It has been observed that homework is not takenseriously and has an average computed score of 7.03/10.00 (C-). The 85% of homework submittedwas mostly done hurriedly prior to submission with help from other students. Even with the

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deficiency in the quality of the homework, it is still a significant factor in assessing student progress.A decline in homework scores may be an early warning for instructor intervention.

The course utilization ratio measure the effectiveness of time spent at college. The averagecourse utilization for this study was around 94% indicating a 6% loss in credit hours. Over theentire length of 125 hours needed to earn a degree, 7.5 hours were lost due to withdrawals or failinggrades. It was hoped that the GPA variable would explain most of course utilization variability aslower course utilization generally meant lower GPA. However, course utilization is still asignificant factor in explaining some of the variability in the AGVT despite GPA presence in theregression model.

The Quantitative Methods topics require application of basic math skills and some statisticalbackground, and Calculus (P1) and Statistics (P2) are the recommended prerequisites. Out of thethree prerequisites P1, P2, and P3 that were included in the multiple regression model, onlyPrecalculus Mathematics I (P3) which is required for the Calculus (P1) and Statistics (P2) courseswas found to significantly influence performance in the Quantitative Methods course. The Calculus(P1) and Statistics (P2) courses did not significantly influence the performance. It was observed thatstudents did not take the prerequisites in the recommended sequence while many others repeated theCalculus (P1) and Precalculus Mathematics I (P3) courses several times to score the required grade(C or higher). Often, students have successfully completed the Quantitative Methods course withouthaving the prerequisites.

Although GENDER was significant during the preliminary statistical analysis, it did notappear in the final multiple regression model (p = 0.1594). Past research has shown mixed resultsin performance between males and females. It is possible that the gender difference was alsoexplained by either GPA or prerequisite Precalculus Mathematics I (P3).

The percentage of days absent (%ABS) is not significant (p = 0.7564). The averagepercentage of days absent was 12% of lecture meetings during the semester. Past research showsan impact of attendance on performance (Shimoff and Catania 2001; Marburger 2001; Devadoss andFoltz 1996). In this course, attendance accounted for 5% of the final course grade. Hence, somestudents with poor attendance record lost points on the course grade although they may have donefairly well at the tests and examination. Furthermore, students who missed classes have theopportunity to catch up during the instructor’s office hours, homework application, and reviewsessions.

The average quiz score (AQZ) was not significant (p = 0.2841). The quiz score contributed10% to the overall course grade. The objective was to provide an opportunity to learn the materialby referring to the text and class notes while completing the quiz. But in actuality, students simpleguessed the answers or sought help from others thereby diminishing effectiveness of the quiz.Hence, non submission of quiz did impact the overall course grade but did not influence the test andexamination performance.

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Can the final multiple regression model be used to predict student performance in theQuantitative Methods course? The scatter plot (Figure 2) of the predicted AVGT versus the actualAVGT shows most points fall very close to the line except for a few outliers at the lower AVGTvalues. It appears that the model provides a good fit and may be used to predict the performanceof a student.

CONCLUSIONS

This study includes an exhaustive literature review of possible factors that could influencethe performance of students in the management science (Quantitative Methods) course and identifiedaround 22 such factors. After a preliminary statistical analysis, nine of these factors were includedas independent variables in the multiple regression model. A stepwise regression analysis resultedin four significant (p < 0.001) variables: GPA, AHW, HE/HA, and P3. The remaining five factorsalthough having influence did not independently contribute significantly to the predictive model.

An objective of this paper is to provide guidelines that may be used by faculty while advisingstudents. Faculty teaching the Quantitative Methods course could do a prior analysis of studentbackground to predict performance. The data for the independent variables could be drawn for thecurrent semester and fitted to the final multiple regression model. The class GPA (GPA), courseutilization ratio (HE/HA), and completion of prerequisite (P3) is available from student transcripts.The average homework score (AHW) will not be available at the beginning of the semester but aconservative estimate could be used. Student whose performance falls below normal could beadvised to take appropriate action such as strengthening basic math skills, seeking tutorial help,improving study habits and class attendance, etc.

As part of the overall advising process, students must be urged to take courses in propersequence to get the maximum benefit from their program. The Department may want to reconsiderits prerequisite policy. Are Calculus (P1) and Statistics (P2) the necessary prerequisite courses, andif so, will a passing grade (D- or higher) be sufficient? Similarly, the instructor could review thegrading policy with greater emphasis on homework as a means of increasing student participation.Since take home quizzes did not impact performance, it could be redesigned or eliminated. Classattendance was not significant for the multiple regression model, however, the correlation matrix(Table 6) shows somewhat strong correlation between attendance and homework as well as quizgrades. Therefore, a strict attendance policy may be necessary to ensure better performance.

This study has limitations. The final multiple regression model explains 51% of the variationin AVGT. Hence, additional factors may need to be included. For example, the current course loadof student could possibly influence the performance. Students carrying a heavy course load maydevote little or no time to this course. Although, no research was found that relates course load andperformance in the management science course, studies in other subject areas have drawn inclusiveresults (Szafran, 2001 and Joy, 1981). Other factors that could influence student performance in the

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management science courses are students’ utilization of faculty office hours and attendance ofreview or recitation session, if available. Additionally, a review of end-of-semester courseevaluations may shed further light into course or instructor factors that may be related to studentperformance.

The sample size of around 300 students was drawn from classes taught by a single instructorand may not reflect the performance over a larger group taught by multiple instructors within theUniversity, or among different colleges and universities. A larger study including multipleinstructors from different institutions would be required to arrive at a general predictive model. Insuch a study, the dependent variable may be affected by different independent variables at theindividual student level and university level. The individual students will be nested withinuniversities thus requiring the application of Multilevel Regression Analysis (Bickel, 2007). Suchlarge data sets could also be analyzed using data mining techniques (Han and Kamber, 2001).

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MOVING TOWARDS A CULTURALLY DIVERSEACCOUNTING PROFESSION

Elizabeth K. Jenkins, San Jose State UniversityMary F. Calegari, San Jose State University

ABSTRACT

This paper discusses the increasing diversity in the accounting profession. Evidence ispresented substantiating that over one third of recent accounting graduates are from ethnic minoritybackgrounds, the majority of whom are Asian/Pacific Islanders. In our university specific data, wefind an even higher percentage (71%) of ethnic minorities receiving accounting degrees, withAsian/Pacific Islanders as the majority group. We also show that over one fourth of new accountinggraduates hired by accounting firms are ethnic minorities of which fifty percent are Asian/PacificIslanders. However, a recent survey by the AICPA indicates that only 4% of partners in accountingfirms are ethnic minorities, again half of whom are Asian/Pacific Islanders. Due to thepredominance of this ethnic group, we discuss several Asian cultural values that are perceived tonegatively impact success and how they can be viewed as positive attributes. Practical tactics arethen prescribed for Asian/Pacific Islanders to be proactive in increasing the probability of attainingpartnership. Finally, recommendations are made for diversity programs to ensure that accountingfirms recognize the importance of promoting a diverse workforce to maintain their competitive edge.

INTRODUCTION

The U.S. population as a whole has seen a shift in demographics to increased minorityrepresentation. According to the 2005 census, the largest growth in the nation’s population wasattributed to Hispanics, up 21% from 2000. Not far behind were significant increases in the Asianpopulation, up 19.2% from 2000 (Kronholz, 2006). Concomitant with the growing diversificationof the general population, U.S. universities are educating a more diverse student population.According to the 2002 U.S. census, 17.5% of African Americans, 9.7% Hispanics, and 44% ofAsian/Pacific Islanders hold a bachelor’s degree (Ying, Lee, and Tsai, 2004).

The national trend towards increasing ethnic diversity transcends to the accountingprofession. Within the discipline, Asian/Pacific Islanders account for the greatest change in newhires. Due to the marked increase of this particular ethnic group, this paper addresses both positiveand negative influences of eastern cultural values on upward career mobility in the accountingprofession and stresses the need for self awareness of an individual’s ethnic heritage. In addition,

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senior management needs to embrace inclusive leadership practices to effectively face the challengesof managing a culturally diverse workforce.

TRENDS IN ACCOUNTING GRADUATES AND THE PROFESSION

The American Institute of Certified Public Accountants (AICPA) has made efforts toincrease the diversity of the accounting profession. In 1969, the AICPA Council formally launcheda national program to integrate the accounting profession and established the Minority InitiativesCommittee (MIC) to implement the following resolutions:

‚ Encourage minority men and women of high potential to attend college and majorin accounting.

‚ Provide educational opportunities for minority men and women to prepare them toenter the accounting profession.

‚ Encourage hiring of minority men and women in order to integrate the accountingprofession in fact as well as ideal.

Four decades after starting this national program, the accounting profession is becomingmore culturally diverse. Table 1 reports the national trends in accounting graduates and hires from1999 to 2007. Panel A indicates that the percentage of minority bachelor’s and master’s graduatesincreased from 23% in 1999-00 to 35% in 2006-07. Panel B presents evidence that 26% of the newaccounting graduates hired by CPA firms in 2006-2007 were minorities, with Asian/Pacific Islanderscomprising half of the total minorities hired (13% of the 26%). This is an increase from 1999-00,where total minorities were 20% and Asian/Pacific Islanders were 10%.

Table 1: National Trends in Accounting Graduates and Hires

Panel A: Bachelor’s and Master’s Graduates

1999-00 2000-01 2001-02 2002-03 2003-04 2006-07

Asian/Pacific Islander 6% 8% 8% 7% 10% 8%

Black/African-American 9% 7% 8% 8% 7% 7%

Hispanic/Latino 5% 5% 5% 6% 7% 11%

American Indian/Alaskan Native 0% 0% 0% 0% 0% 1%

Other (mixed race) 3% 5% 7% 7% 10% 8%

Total Ethnic 23% 25% 28% 28% 34% 35%

White 77% 75% 72% 72% 66% 65%

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Table 1: National Trends in Accounting Graduates and Hires


Panel B: New Accounting Graduates Hired by CPA Firms

Asian/Pacific Islander 10% 8% 8% 9% 12% 13%

Black/African-American 3% 3% 3% 5% 3% 8%

Hispanic/Latino 7% 6% 6% 4% 8% 4%

American Indian/Alaskan Native 0% 0% 0% 0% 0% 1%

Total Ethnic 20% 17% 17% 18% 23% 26%

White 79% 82% 82% 81% 76% 72%

Other/Unknown 1% 1% 1% 1% 1% 2%

Source: The Supply of Accounting Graduates and the Demand for Public Accounting Recruits - 2008

The trend of increasing numbers of Asian/Pacific Islander accounting graduates is even morepronounced at our university, San Jose State University (SJSU). SJSU is part of the California StateSchool System. Table 2 reflects the trend in accounting degrees awarded at SJSU from 1998 to2008. The total minorities increased from 63% (1998-99) to 71% (2007-08). Most interesting isthe increase in Asian/Pacific Islanders receiving accounting degrees from 48% in 1998-99 to 60%in 2007-08. In 2007-08, Asian/Pacific Islanders made up almost 85% of the total minority group.

Table 2: Trends in Accounting Degrees (Bachelor’s) Awarded at San Jose State University

1998-1999

1999-2000

2000-2001

2001-2002

2002-2003

2003-2004

2004-2005

2005-2006

2006-2007

2007-2008

Asian/Pacific Islander 48% 41% 44% 49% 41% 37% 52% 49% 54% 60%

Black/African-American 5% 5% 3% 1% 2% 3% 2% 2% 2% 2%

Hispanic/Latino 9% 12% 13% 9% 11% 10% 10% 8% 9% 9%

American Indian/Alaskan Native 1% 1% 0% 1% 1% 0% 1% 1% 0% 0%

Total Ethnic 63% 59% 60% 60% 55% 49% 64% 59% 66% 71%

White 23% 24% 30% 20% 25% 23% 16% 20% 21% 16%

Other/Unknown 14% 17% 11% 20% 20% 28% 20% 21% 14% 13%

Source: SJSU Office of Institutional Research Website (www.oir.sjsu.edu

Table 3 reports the national trends in CPA firm demographics from 2003 to 2007. Panel Apresents the professional staff demographics by firm size. For all firms, the percentage of minoritiesincreased 1% from 10% in 2003-04 to 11% in 2006-07. Similarly, the percentage of Asian/PacificIslanders increased 1% from 5% in 2003-04 to 6% in 2006-07. The results from Panel A indicatethat the larger CPA firms tend to be more diversified than smaller firms. In 2006-07, firms with over200 members were made up of 16% minorities, 10% of whom are Asian/Pacific Islanders. In

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contrast, firms with less than 10 members, total minorities were 8%, with 4% being Asian/PacificIslanders.

Panel B of Table 3 reports the demographics of CPAs by firm size. The results are slightlylower than those reported in Panel A. For all firms, the percentage of minority CPAs decreased by1% from 8% (2003-04) to 7% (2006-07). However, the percentage of Asian/Pacific Islander CPAsremained constant at 4%. Similar to Panel A, larger CPA firms are more diversified than smallerfirms. In 2006-07, firms with over 200 members had 12% minority CPAs, with 8% beingAsian/Pacific Islanders. In contrast, firms with less than 10 members had 6% minority CPAs, with3% being Asian/Pacific Islander.

Panel C presents partner demographics by firm size. For all firms, the percentage of minoritypartners remained at 5% from 2003 to 2007, where 2% were from Asian/Pacific Islanderbackground. Contrary to Panels A and B, partner diversity does not increase with firm size. In fact,for firms with less than 10 members, 7% of partners were from minority backgrounds in 2006-07,compared to 4% for CPA firms with more than 200 members.

Table 3: National Trends in CPA Firm Demographics

Panel A: Professional Staff Demographics by Firm Size

All Firms <10 10-49 50-200 >200

2003-2004

2006-2007

2003-2004

2006-2007

2003-2004

2006-2007

2003-2004

2006-2007

2003-2004

2006-2007



Hispanic/Latino 3% 3% 4% 2% 3% 2% 2% 1% 4% 3%


Total Ethnic 10% 11% 10% 8% 8% 12% 8% 7% 18% 16%

White 89% 80% 89% 91% 92% 87% 91% 91% 82% 59%

Other/Unknown 1% 9% 1% 1% 0% 1% 1% 2% 0% 25%

Panel B: CPAs Demographics by Firm Size



Hispanic/Latino 3% 2% 3% 2% 2% 1% 2% 0% 3% 2%


Total Ethnic 8% 7% 7% 6% 5% 8% 6% 4% 12% 12%

White 92% 87% 92% 93% 95% 91% 93% 95% 88% 68%

Other/Unknown 0% 6% 1% 1% 0% 1% 1% 1% 0% 20%

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Table 3: National Trends in CPA Firm Demographics


Panel C: Partners Demographics by Firm Size



Hispanic/Latino 2% 2% 3% 3% 1% 0% 1% 0% 1% 1%


Total Ethnic 5% 5% 6% 7% 2% 3% 2% 0% 4% 4%

White 95% 91% 94% 91% 98% 95% 99% 96% 96% 80%

Other/Unknown 0% 4% 0% 2% 0% 2% 0% 4% 0% 16%

Source: The Supply of Accounting Graduates and the Demand for Public Accounting Recruits – 2005, 2008

The evidence reported in Tables 1 and 3 indicate that the evolution towards diversity in theaccounting profession has been restricted to the lower levels of CPA firms and with no concomitantincrease to date at the partnership level. Chris Yahng, the 2005-2006 California CPA Society chair,represents the first Asian American to assume this leadership position. He is quoted as saying,

“While we have greater numbers of women and ethnic minorities filling the ranksof the profession than we did 30 years ago, we aren’t seeing the corresponding shiftinto leadership positions” (Ascierto, 2005).

During his term, one of his goals was to work with local chapters to identify and encourage futureleaders that are more representative of the cross-cultural workforce.

The gender issue of attaining representative leadership roles in both the accountingprofession as well as corporate America has long been of interest in research studies and thefinancial press. In a census of Fortune 500 companies, Catalyst (a women’s research and advisorygroup) found that the number of women moving up the corporate pipeline has increased over thepast decade (Dobrzynski, 2006). Similarly, the AICPA reports that the percentage of womenpartners in CPA firms has increased over the last decade from 12% to 19% (New Accountant, 2006).These results suggest that women appear to have broken the leadership barriers and havesuccessfully climbed to the top of the corporate ladder.

Although women have made strides to crack the glass ceiling, only time will tell if theincreasing number of ethnic minorities will reach the corner office at the appropriate proportionaterate. In the meantime, steps must be taken by employees and employers to prevent the developmentof a “bamboo ceiling” for the growing numbers of Asian/Pacific Islanders currently entering theaccounting field.

Calegari and Jenkins (2006) find that cultural influences and ethnic background may befactors that impact success in the accounting profession. In a survey of accounting alumni, Calegari

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and Jenkins find significant differences between ethnic groups in their perceived stress management,leadership, critical thinking, and communication skills. These skills are the very traits necessary tosuccessfully climb to the top rung of the professional ladder. In this paper, we focus on theAsian/Pacific Islander group since they make up the majority of the total minority group.

ASIAN CULTURAL VALUES

While Asians face the same early problem as women in terms of being initiallyunderrepresented in positions of power and responsibility in public accounting, they also facedifferent hurdles to reach success which may be attributable to deeply ingrained eastern culturalvalues. Without question, individual differences do exist within any ethnic group and behaviors arenot generalizable to any diverse group of people. However, prior studies have identified traditionalAsian values profoundly impacted by the Chinese philosopher, Confucius. Five Asian culturalvalues emphasized in numerous sources include:

‚ Respect for authority‚ Collectivism‚ Self-control/restraint‚ Humility‚ Educational and occupational achievement

Respect for authority begins at a young age, when children are taught to respect adults andto speak softly. Confucius said, “A young man should serve his parents at home and be respectfulto elders outside his home.” This learned behavior transcends to adulthood with deference to anyonein a position of authority. In the classroom, respect for the teacher is manifested by not speakingup. In the workplace, the supervisor is given respect regardless of competence. Body language isalso influenced by this particular cultural value. The custom of avoiding direct eye contact isconsidered an act in deference to authority.

Collectivism refers to a tendency to place the best interest of the group over that of anindividual. In the workplace, this philosophy translates into group decision-making and consensusbuilding. Individuals are discouraged from standing out or attracting attention.

This same tendency is also tied to deep rooted cultural values of self-control and humility.While hard work and diligence are encouraged, self promotion is a discouraged behavior. Thisattitude may be counterproductive to the climb up the partnership ladder where high profile andvisibility are essential to success.

Education is highly revered in the Asian culture. Holding several higher education degreesis not atypical. However, achievement is defined as advancing through formal education programsas opposed to hands-on knowledge attained in the workplace.

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Although knowledge in multiple disciplines is valued by the accounting profession, theemphasis in the 21st century is away from technical skills and towards strategic planning. Thesemanagement skills can best be developed on the job as opposed to further education in a classroomsetting.

TURNING CULTURAL VALUES INTO ASSETS

The aforementioned cultural values can be perceived as liabilities that negatively impactsuccess. However, as the old adage states, there are two sides to every coin. Each of these valuescan be viewed as positive attributes as well. To achieve professional success, individual assessmentis necessary to determine the strengths and weaknesses of their cultural values and turn them in apositive direction. Respect for authority generally results in a strong sense of loyalty. Loyalty tothe firm as well as to the client is a valued asset in public accounting. However, the questionremains is this attribute properly rewarded in terms of promotion?

Collectivism and self control are tied to the emphasis on harmony in the Asian culture. Thestrong desire to avoid conflict translates into an employee that is easy to work with in a collaborativesetting.

The Asian culture also values humility as reflected in a famous Asian proverb, “the loudestduck gets shot.” Although this attribute is counterproductive to individual recognition, the CPA firmmay greatly benefit from employing a team player. A strong sense of teamwork often gets the jobdone, over and above self aggrandizement.

Finally, the high value placed on education in the Asian culture transcends into theworkplace. The 21st century accountant needs the intellectual skills for critical thinking in order tosucceed in the profession. The educational process should entail the development of creativity,innovation, and out-of-box thinking. This can be accomplished through projects, group work, andcases. Also, the inclusion of internships in the accounting programs provides students with valuablehands on experience in the business world.

An individual with an Asian background does not have to become a different person in orderto thrive in the public accounting culture. However, to reach the top, development of culturalcompetencies is essential. This process requires identification of skills needed in the workforce thatmay be outside of the individual’s cultural comfort zone. For example, strong communications skillsare an essential attribute for achieving the rank of partnership. These skills needed to succeed (i.e.client presentations, marketing accounting services, conducting meetings) must be developed at anearly stage in one’s career. Each individual must identify their unique needs for developmentthrough self-assessment.

In summary, success is predicated on understanding an individual’s strengths andweaknesses. This process of self assessment is important to any individual regardless of race orculture. With respect to the Asian culture, the emphasis on harmony, collectivism, and self control

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may pose challenges in a predominantly Socratic workplace. In order to reach the partnership level,the individual not only must maintain the richness of their Asian heritage, but also arm themselveswith new behaviors necessary to meet the challenges of public accounting. According to Huyn(2005), “Self-awareness is the first and most important step in breaking the bamboo ceiling.”

INDIVIDUAL PRACTICAL TACTICS TO SUCCEED

Beyond the important issue of self-awareness, there are numerous practical tactics thatAsian/Pacific Islanders should pursue early in their career in order to increase the probability ofsuccess in the field of accounting. These include the following:

‚ Find and maintain mentor relationships‚ Build a network‚ R&R – Be resilient and be a risk taker‚ Identify Asian friendly firms

A mentor is someone who coaches you on office politics, workplace issues, and careerbuilding techniques on an ongoing basis. The goal is to find several mentors not necessarily ofAsian descent. The most important aspect of a quality mentoring relationship is good chemistry.Seek out people that you respect and that possess qualities that you need to develop yourself. Beproactive in approaching potential mentors and setting up meetings. Establish milestones tomonitor your success over periods of time. Utilize the mentor to obtain feedback regardingprofessional behavior and skills. The mentor can be viewed as a trusted advisor and help assess yourdevelopment of technical, interpersonal, leadership and functional skills. Internal mentors can proveinvaluable in helping you understand the political climate of the firm.

Networking is a time tested skill necessary to succeed in the American business world.However, the practice of networking may be uncomfortable to less acculturated Asians. Askingstrangers for help goes against eastern values. However, networking is an essential aspect ofreaching the corner office. This process may be facilitated through Asian Pacific organizations suchas the National Asian American Society of Accountants. The mission of this organization, foundedin 2004, is to help Asian American accountants advance business development opportunities. Aspart of the process, a system should be developed to organize and maintain contacts either throughemail, regular mail or phone calls. Cultivating a deep and broad network has a more positive impacton success. Networking is not just about job changes, but more importantly, potential clients for thefirm. Asian heritage is a unique asset and should be used to build bridges between the culturalcommunity and the business community. Minority advocacy groups can provide access toleadership training and other career development forums best suited to unique Asian cultural needs.

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Career resiliency means the ability to weather enumerable storms over time and bounce backin the face of failure. Asians need to use their resiliency in overcoming failures as well as falsejudgments. Jeanne Dienfenderfer, a Korean American senior vice president at VerizonCommunications offers the following advice. “Even if I had been discriminated against earlier inmy career, I never felt like a victim. If it happened, I bounced back and remained assertive.” Highprofile client assignments carry a certain amount of risk. Yet with that risk, there yields higherreward in promotion and recognition. Embracing the notion of shame in failure will only result inconservative actions ultimately leading to career roadblocks.

In the search for a best fit employer, due diligence is necessary to determine if the companieswalk the talk. Communicate with people in the organization to determine if the company hasopportunities for development that lead to inclusive leadership. Also, it is important to recognizecurrent diversity trends in practice that may affect the Asian’s ability to reach the top.

Implementation of these tactics takes time and effort by the individual. In addition, a keyfactor to their success will depend on accounting firms embracing the move towards increaseddiversification at all levels of the firm.

EFFECTIVE ACCOUNTING FIRM DIVERSITY PRACTICES

Accounting firms must implement diversity policies to help open the door to success for thegrowing numbers of ethnic minorities. Some firms have already initiated several measures towardsdiversity practices. In order to achieve inclusive leadership, all of the following are stronglyrecommended:

‚ Specialized recruitment practices‚ Support formal and informal mentor programs‚ Provide effective training‚ Open access to top assignments‚ Ensure senior management buy-in to these practices

Creating a strong recruiting program that promotes diversity is essential towards moving inthe right direction. Past practices of getting referrals from employees, traditional outsideorganizations, and campus visits are not only passé but can foster increased homogeneity. Firmsneed to extend recruiting efforts into minority networking organizations and student culturalorganizations. There is a long list of networking organizations specific to Asian ethnic backgroundsas well as other ethnic groups. Just sending recruiters to ethnic specific organizations is notsufficient. Hiring results must be closely monitored and successful efforts properly rewarded if thefirm is committed to changing their demographics.

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Upon hiring a more diverse workforce, the CPA firms must then create appropriate supportgroups to mentor junior minority professionals. One suggestion is to offer brown bag luncheons asa forum for discussions related to problems minorities are facing and strategies to overcomeobstacles. Senior management should attend these sessions so that individuals have a chance tocommunicate their concerns and needs and management becomes aware of their unique challenges.Over time, formal mentor programs should be developed for those minorities that have demonstratedpartnership potential.

Diversity training should be required for all levels from new recruits to partners. Thispractice may require hiring an internal diversity expert to coordinate initiatives for minorities. Topmanagement however, should be held accountable for results by tying compensation and incentivesto meeting the diversity goals established in the training sessions. The firms also need to providespecialized training programs for individual ethnic groups. The unique needs can be identified inthe mentor sessions and programs can be tailored to address shortfalls. For example, if soft skillsneed sharpening in order to reach partnership level, then professional education should incorporatethis skill set beyond merely traditional technical training.

In public accounting, reaching the partnership is highly dependent upon the clientassignments and the engagement team. Top management needs to monitor the informal networksthat may promote exclusivity in assignments. Efforts must be made to provide career-enhancingopportunities in a fair and equitable fashion to all qualified individuals. Minorities must beencouraged to accept stretch assignments if any resistance is observed.

Above all, senior partners must truly believe and commit to the idea that achieving inclusiveleadership in the future by implementing effective diversity practices is a mission critical to survival.With the globalization of business, management and leadership teams need to be diverse so they canrelate and respond to the issues that their clients are dealing with. Changing the traditional CPAinfrastructure to one that supports upward mobility for Asians and other ethnic groups requires apositive buy-in from top tier management. The importance of moving towards diversity must becommunicated from the top down in every manner, including: memos, meetings, training,compensation, recruiting. All partners must understand the reality that diversity and inclusiveleadership is a business strategy for success and not just a politically correct program.

CONCLUSION

To maintain their competitive edge, companies need to recognize the importance ofmanaging and promoting a diverse workforce. Based on the findings in the study by the AICPA,this statement rings loud and clear for CPA firms. The evidence is clear. The demographics of theaccounting workforce are changing faster than human resources policies can keep pace. It is up tothe partnership to abandon archaic policies about what motivates and retains people and initiateeffective practices that fit the reality of their multicultural workforce.

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By 2050, the prediction is that the majority of Americans will be from non-Caucasianbackgrounds. Eventually, corporations will evolve inclusive leadership as a necessity for survival.In the meantime, individual Asians can be proactive to accelerate the move up the ladder to thepartnership rung.

REFERENCES

American Institute of Certified Public Accountants (AICPA). 2005. The Supply of Accounting Graduates and theDemand for Public Accounting Recruits – 2005. New York, NY.

American Institute of Certified Public Accountants (AICPA). 2008. The Supply of Accounting Graduates and theDemand for Public Accounting Recruits – 2008. New York, NY.

Ascierto, J. 2005. Opening Door, CALCPA Chair Creates Opportunity, Focuses on Diversity. California CPA(August).

Calegari, M. F. and E. Jenkins. 2006. Can Cultural Influences Affect Your Success in the Accounting Profession? NewAccountant Magazine 717.

Dobrzynski, Cherchez la Femme. 2006. Wall Street Journal, New York, N.Y. (August 4): A.16.

Hyun, J. 2005. Breaking the Bamboo Ceiling. Harper Collins, New York, NY.

Kronholz, June. 2006. Hispanics Gain in Census. Wall Street Journal (May 10).

Women Making Strides in Becoming Leaders in Public Accounting. 2006. New Accountant (February).

Ying, Y., P. Lee, and J. L. Tsai. 2004. Inventory of College Challenges for Ethnic Minority Students: PsychometricProperties of a New Instrument in Chinese Americans. Cultural Diversity and Ethnic Minority Psychology,10: 351-364.

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